Facial Recognition

Face expression recognition technology is one of the most recently developed fields in machine learning and has profoundly helped its users through forensic, security, and biometric applications. Many researchers and program developers have allocated their time and energy to figure out various techniques which would add to the technology’s functionality and accuracy. Face expression recognition is a complicated computational process in which is implemented via analyzing changes in facial traits that follow different emotional reactions. This paper endeavors to inspect accuracy ratio of six classifiers based on Relief-F feature selection method, relying on the utilization of the minimum quantity of attributes. The classifiers in which the paper attempts to inspect are Multi-Layer Perceptron, Random Forest, Decision Tree, Support Vector Machine, K-Nearest Neighbor, and Radial Basis Function. The experiment illustrates that K-Nearest Neighbor is the most accurate classifier with the to...

Facial Recognition Technology (FRT) emerged as a solution to address several contemporary needs of identifying and verifying an individual's identity. It fulfills the biometric system requirements, which tries to recognize the status of an individual by using features distinctive from the body and functionalities that are more familiar with the operation of visual surveillance. This report develops an analysis that connects the socio-scientific literature with the technology on FTR and addresses the concerns and challenges attached to the development, evolutional, and the operational usage that are specific, the contexts, and goals. It highlights the problematic, potentials, and the limitations of the technology. The report also identifies the tasks that the FRT seems to be ready to deploy, the areas with specified obstacles, and how to overcome them by the developments of future technology and operating procedures of sound. It also addresses specific issues that appear to interact with technology. It is also concerned with the ethical considerations on the extent of efficacy. The report's findings are further broken down into different categories to understand further the evaluation, performance, operation, policy concerns, and political and moral operations. So far, the technology has been implemented in several fields to enable monitoring and surveillance. In this background, the report also addresses the FRT alterations on the nature of the authoritarian and lines that are oppressive in the United States as the primary focus.

New research into human-computer interaction seeks to consider the consumer's emotional status to provide a seamless human-computer interface. This would make it possible for people to survive and be used in widespread fields, including education and medicine. Multiple techniques can be defined through human feelings, including expressions, facial images, physiological signs, and neuroimaging strategies. This paper presents a review of emotional recognition of multimodal signals using deep learning and comparing their applications based on current studies. Multimodal affective computing systems are studied alongside unimodal solutions as they offer higher accuracy of classification. Accuracy varies according to the number of emotions observed, features extracted, classification system and database consistency. Numerous theories on the methodology of emotional detection and recent emotional science address the following topics. This would encourage studies to understand better ph...

This study aims to discuss the limitations in the facial analysis
of closed-circuit television (CCTV) images, including the use
of morphological and anthropometric methods, and to analyze the level of effectiveness of CCTV images, taking into account any negative factors that may affect the forensic anthropologist/forensic facial examination expert’s conclusion. Ten forensic experts from different forensic laboratories and universities participated in this research. The experts were asked to compare the query CCTV images, which were of varied quality, with the target images. The results suggest that a high error rate and low-level assessment are provided by low quality CCTV images, whereas morphological and anthropometric analysis can be performed more accurately and correctly with the high level of assessment provided by moderate/reasonable quality CCTV images. To use morphological and anthropometric methods efficiently and take maximum advantage of the use of security cameras in forensic facial identification, it is suggested to set a CCTV recording standard for high quality recordings.

Security has become a major issue globally and in order to manage the security challenges and reduce the security risks in the world, biometric systems such as face detection and recognition systems have been built. These systems are capable of providing biometric security, crime prevention and video surveillance services because of their inbuilt verification and identification capabilities(Hjelmas & Kee Low, 2001). This has become possible due to technological advancement in the fields of automated face analysis, machine learning and pattern recognition (Wojcik et al, 2016). In the paper, we review some biometric and facial recognition techniques.

ABSTRACT: As we know the tradition approach of attendance, takes quite long to take attendance and pronounce each and everyone’s name properly of a bulk of students. And in the changing world we must have to update our attendance system in a smarter way with speed and efficiency to reduce the time required to take attendance in our traditional way. Here, we are presenting an automated attendance management system using Raspberry Pi and NFC which is a smarter and more efficient way.with the help of such system the attendance management system in school/colleges/universities and hence reducing the time required for attendance in class. This system is applicable to not only students but also teachers, employees, workers.

Stimuli that resemble humans, but are not perfectly human-like, are disliked compared to distinctly human and non-human stimuli. Accounts of this "Uncanny Valley" effect often focus on how changes in human resemblance can evoke different emotional responses. We present an alternate account based on the novel hypothesis that the Uncanny Valley is not directly related to 'human-likeness' per se, but instead reflects a more general form of stimulus devaluation that occurs when inhibition is triggered to resolve conflict between competing stimulus-related representations. We consider existing support for this inhibitory-devaluation hypothesis and further assess its feasibility through tests of two corresponding predictions that arise from the link between conflict-resolving inhibition and aversive response: (1) that the pronounced disliking of Uncanny-type stimuli will occur for any image that strongly activates multiple competing stimulus representations, even in the ...

In modern times the quantity of on road vehicles is expanding very quickly. Most of the time, it is important to verify the identity of these vehicles for authorization of the transit regulation, overseeing parking garages. it is hard to check this colossal number of moving vehicles physically. Subsequently, building up a precise automatic license plate recognition model (ALPR) including character recognition is important to ease the issues mentioned above. We have developed a model based on multiple types of license plates from different countries. The dataset of images was trained using Yolov4 which uses CNN architectures. Character recognition was done using the Tesseract OCR after multiple image pre-processing techniques and morphological transformations. The proposed program has obtained an accuracy of 92% in license plate detection and 81% in character recognition.

Face and facial pattern detection is an active research area that is useful for many practical applications. In this paper, we present an innovative technique for eye detection using Augmented Dynamic Time Warping (ADTW) algorithm. Dynamic Time Warping (DTW) is a reliable algorithm that can perform similarity matching between two sequences but it requires supplimnetry techniques to be effective and efficient when used as a pattern detection tool. Therefore, for template matching in a facial pattern detection, the DTW is augmented with proposed image processing strategy along with a proper weighting scheme to increase its efficiency and accuracy. Our proposed ADTW overcomes some of the shortcomings associated with the traditional dynamic time warping and hence improves the alignment of the warping path of the sequences. The results of the implementation of the ADTW to detect eyes in facial images of subject with and without glasses show a marked improvement in detection accuracy when compared with that of the traditional DTW. © 2012 ICIC International.

www.ijicic.org/10-08069-1.pdf

Direct human intervention in AI reports and mitigating outcomes within their contest shall be regarded as fundamental factors in this development. The safeguards offered by Article 22 GDPRsupport this view when stating that “the data subject shall have the right not to be subject to a decision based solely on automated processing”.

The human resource (HR) domain contains various types of privacy-sensitive textual data, such as e-mail correspondence and performance appraisal. Doing research on these documents brings several challenges, one of them anonymisation. In this paper, we evaluate the current Dutch text de-identification methods for the HR domain in four steps. First, by updating one of these methods with the latest named entity recognition (NER) models. The result is that the NER model based on the CoNLL 2002 corpus in combination with the BERTje transformer give the best combination for suppressing persons (recall 0.94) and locations (recall 0.82). For suppressing gender, DEDUCE is performing best (recall 0.53). Second NER evaluation is based on both strict de-identification of entities (a person must be suppressed as a person) and third evaluation on a loose sense of de-identification (no matter what how a person is suppressed, as long it is suppressed). In the fourth and last step a new kind of NER dataset is tested for
recognising job titles in tezts.

In this paper, the proposed system has demonstrated three ways of detecting alcohol level in the body of the car driver and prevent car driver from driving the vehicle by turning off the ignition system. It also sends
messages to concerned people. In order to detect breath alcohol level MQ-3 sensor is included in this module along with a heartbeat sensor which can detect the heart beat rate of driver, facial recognition using webcam & MATLAB and a Wi-Fi module to send a message through the TCP/IP App, a Raspberry pi module to turn off the ignition and an alarm as prevention module. If a driver alcohol intake is more than the
prescribed range, set by government the ignition will be made
off provided either his heart beat abnormal or the driver is
drowsy. In both the cases there will be a message sent to the
App and from the App you can send it to family, friend, and
well-wisher or nearest cop for the help. The system is
developed considering the fact if driver is drunk and he needs
a help, his friend can drive the car if he is not drunk. The
safety of both the driver and the surroundings are aimed by
this system and this aids in minimizing death cases by drunken
driving and also burden on the cops.
Keywords — Drowsy state detection, Drunken state Detection,
Internet of Things, Facial recognition, Prevention models,
Raspberry Pi.

Abstract: Facial Recognition, the biggest breakthrough in Biometric identification and security since fingerprints, uses an individual’s facial features to identify and recognize them. A technology that seems too farfetched taken straight from a science fiction novel is now available in smartphones in the palm of our hands. Facial Recognition has gained traction as the primary method of identification whether its mobile phones, smart security systems, ID verification or something as simple as login in a website. Recent strides in facial recognition technologies have made it possible to design, build and implement a facial recognition system ourself. Using Computer Vision and machine learning libraries like Facial Recognition and Dlib, we can create a robust system that can detect faces and then match and identify it with a database of pre-loaded facial data to successfully recognize them. This study conducted a literature review of these aforementioned technologies and various other...

Face recognition technologiesstate of play & technological frontiers Nowadays a simple image of our face could reveal a lot more about us than we would like people to know. This is possible thanks to facial recognition technologies (FRT) that can trace a person's identity and other information if the image of his face can be found in some database, which is very likely, since about 3.81 billion people are active users of social media i. FRT has been studied and tested since the 1960s, however it had failed to break through in the application field as it was unreliable and inaccurate due to technological limitations. Nevertheless, since a little less than a decade 1 , facial recognition has started to be more and more present not only in airports and public open spaces but also implemented in banks' services, computers, smartphones etc. Certainly, most of the credit goes to Artificial Intelligence (AI). The goal of Artificial Intelligence is to emulate human intelligence, and Jeff Mc Frockman defines it as "the ability of machines to make decisions and learn in a similar manner as humans" ii. AI refers to a computer system that can perform tasks that normally require human intelligence such as speech recognition, visual perception, decision making, and language translation. But talking about artificial intelligence applied to facial recognition technologies is rather reductive and generic as it is not possible to understand how this works without talking about Machine learning (ML) and Deep Learning (DL).

Essay accompanying the exhibition 'Persona: Four Self-Portraits', including work by Karenne Ann, Greg Neville, Sean Payne and Kirsten Perry.

Every self-portrait is a form of propaganda, even when the mode is supposedly confessional. These four artists seek to remove themselves from temptation by either adopting the impersonal, anonymously institutional image or essaying the process of vision itself rather than its ostensible subject.

This study, commissioned by the European Parliament’s Policy Department for Citizens’ Rights and Constitutional Affairs at the request of the LIBE Committee, examines the impact on fundamental rights of Artificial Intelligence in the field of law enforcement and criminal justice, from a European Union perspective. It presents the applicable legal framework (notably in relation to data protection), and analyses major trends and key policy discussions. The study also considers developments following the Covid-19 outbreak. It argues that the seriousness and scale of challenges may require intervention at EU level, based on the acknowledgement of the area’s specificities.

In modern times the quantity of on road vehicles is expanding very quickly. Most of the time, it is important to verify the identity of these vehicles for authorization of the transit regulation, overseeing parking garages. it is hard to check this colossal number of moving vehicles physically. Subsequently, building up a precise automatic license plate recognition model (ALPR) including character recognition is important to ease the issues mentioned above. We have developed a model based on multiple types of license plates from different countries. The dataset of images was trained using Yolov4 which uses CNN architectures. Character recognition was done using the Tesseract OCR after multiple image pre-processing techniques and morphological transformations. The proposed program has obtained an accuracy of 92% in license plate detection and 81% in character recognition.

Facial Recognition, the biggest breakthrough in Biometric identification and security since fingerprints, uses an individual's facial features to identify and recognize them. A technology that seems too farfetched taken straight from a science fiction novel is now available in smartphones in the palm of our hands. Facial Recognition has gained traction as the primary method of identification whether its mobile phones, smart security systems, ID verification or something as simple as login in a website. Recent strides in facial recognition technologies have made it possible to design, build and implement a facial recognition system ourself. Using Computer Vision and machine learning libraries like Facial Recognition and Dlib, we can create a robust system that can detect faces and then match and identify it with a database of pre-loaded facial data to successfully recognize them. This study conducted a literature review of these aforementioned technologies and various other advancements in the field of computer vision facial recognition by other scholars in their research papers. This paper analyzes domains to understand the working of these machine learning models and their different implementations in facial recognition systems. The research conducted by us during this review will be paramount in creating a proof-of-concept prototype facial recognition system.

The purpose of this paper is to gain a better understanding of
user acceptance of Biometric Technologies (BT) at outdoor
music festivals in the United Kingdom. While research on such
technologies, such as facial recognition is limited in the events
context, they have already been deployed at music festivals to
deal with issues of security, safety and crowd management.
Using an extended Technology Acceptance Model (TAM), a
self-administered questionnaire was completed by young
adults in the United Kingdom who had previously been to a
music festival. The study found factors such as privacy, reliability and accuracy did not have a significant impact on user
acceptance. Other factors, such as trust, compatibility and convenience were found to have a significant positive impact on
perceived ease of use, perceived usefulness and attitude to
use. As the findings indicate that accuracy and privacy do not
impact BT acceptance, the paper explores how organizers can
be transparent and accountable as to their intentions to use
BT, so as to justify the usefulness of BT to attendees, artists,
regulators and authorities.

The Predictive Casino is a casino that utilizes the latest technological developments to connect with its customers to deliver an exceptional personalized experience to each and every one of its patrons. Today, technology such as AI, Machine Learning, Augmented Reality, IoT, Real-time stream processing, social media, and wearables are altering the Customer Experience (CX) landscape and casino operators need to jump aboard this fast moving technology or run the risk of being left out in the cold.
The Predictive Casino reveals how these and other technologies can help shape the customer journey. The book details how the five types of analytics—descriptive, diagnostic, predictive, prescriptive, and edge analytics—affect not only the customer journey, but also just about every operating function of the casino.
Facial recognition technology can spot a customer stepping onto a casino bus at the Macau/China border and that set off alerts that can notify a host on the floor, a restaurant manager, a dealer, or even the hotel’s GM should the player be a high-end VIP. A whole other sequence of events gets triggered as the player’s favorite table is prepared, his favorite, and his or her Theo gets added to a real-time table games revenue management model that takes into account his personal play. Labor needs are also considered and alerts can be sent to the required or unneeded staff.
An IoT connected casino can make its operations smart. Connected devices can help with inventory optimization, supply chain management, labor management, waste management, as well as keep its data centers green and its energy use smart. 
Social media is no longer a vanity platform, but rather a place to both connect with current customers as well as court new ones. It is also a powerful branding channel that can be utilized to both understand a casino's position in the market, as well as a place to benchmark its position against its competitors.
Today, technology moves at break-neck speed and it can offer the potential of anticipatory capabilities, but it also comes with a confusing variety of technology and technological terms--Big Data, Cognitive Computing, CX, Data Lakes, Hadoop, Kafka, Personalization, Spark, etc., etc. The Predictive Casino will help make sense of it all, so that a casino executive can cut through the confusing technological jargon and understand why a Spark-based real-time stream processing data stream might be preferable over a TIBCO one, or an IBM one. This book will help casino executives break through the technological clutter so that they can deliver an unrivaled customer experience to each and every patron coming through their doors.

In this project we have implemented the automated attendance system using MATLAB. We have projected our ideas to implement “Automated Attendance System Based on Facial Recognition”, in which it imbibes large applications. The application includes face identification, which saves time and eliminates chances of proxy attendance because of the face authorization. Hence, this system can be implemented in a field where attendance plays an important role.

I am also adding the link to the code I used for the project since a lot of students have asked me the codes so far.
https://www.dropbox.com/s/3nv20kwrc9axk2y/MATLAB%20Code.zip?dl=0

Biometrics is the technology of identifying uniquely human subjects by means of measuring and analyzing one or more intrinsic behavioral or physical traits. These human body characteristics include fingerprints, voice patterns, eye retinas and irises, facial patterns and hand measurements. Biometric systems include applications making use of biometric technologies and which allow the identification automatically, verification or authentication of a natural person. In principle, the processing of personal data involving the use of a biometric system is considered by privacy experts to be only justified in places demanding a high level of security and strict identification procedures.

An Intelligent Virtual Assistant (IVA) or Intelligent Personal Assistant (IPA) is a software agent that can perform tasks or services for an individual based on commands or questions. In future all the electronic gadgets are operated by using virtual assistant which is anything but difficult to get to yet it needs in security. Project aims to provide security for virtual Assistant (VA) through facial recognition. The framework enables just approved users to access voice commands. By this we can get protection and security for virtual assistant (VA). Users can ask their help addresses like time, date and climate and find solution to the inquiries. This virtual assistant causes us to send email through voice commands and it also takes notes from voice commands with security. It gives access to the unapproved user to enlist with the required consent from the administrator. It is can exchange the pictures and documents just by using voice commands. It will take photographs using camera when we use the fitting voice commands. Various users in a family can get access to the virtual Assistant by facial recognition module.

Este proyecto tiene como objetivo principal la realización de diferentes pruebas en un algoritmo de reconocimiento facial existente utilizando como herramienta el software MatLab, esto con el objetivo de identificar cuáles pueden ser las características óptimas que debe de tener una imagen para que el algoritmo pueda identificar de manera correcta los rasgos faciales (ojos,nariz y boca). Para la realización de estas pruebas se establecieron 6 características diferentes para clasificar las imágenes, estas fueron buena iluminación,mala iluminación,rostro de lejos,rostro de cerca,perfil y rostro mostrado de manera parcial. Además se hicieron pruebas con la misma imagen usando dimensiones de 200x200px hasta 800x800px, a color y en blanco y negro. En el algoritmo de reconocimiento facial la única modificación que se realizó fueron los parámetros del threshold cambiando el valor a 5,10,15 y 20. Index Terms-Algoritmo de reconocimiento facial, procesamiento de imagen,threshold

A live automated facial recognition technology, rolled out in public spaces and cities across the world, is transforming the nature of modern policing.  In R (on the application of Bridges) v Chief Constable of South Wales Police, decided in August 2020 (‘Bridges’) – the first successful legal challenge to automated facial recognition technology worldwide - the Court of Appeal in the United Kingdom held that the use of automated facial recognition technology by the South Wales Police was unlawful. This landmark ruling can set a precedent and influence future policy on facial recognition in many countries. Bridges decision imposes some limits on the previously unconstrained police discretion on whom to target and where to deploy the technology. Yet, while the decision demands a clearer legal framework to limit the discretion of police who use such technology, it does not, in principle, oppose the use of facial recognition technology for mass-surveillance in public places, nor for monitoring political protests. To the contrary, the Court accepted that the use of automated facial recognition in public spaces to identify very large numbers of people and to track their movements is proportional to law enforcement goals. Thus, the Court dismissed the wider impact and significant risks posed by using facial recognition technology in public spaces; it underplayed the heavy burden placed on democratic participation and the rights to freedom of expression and association, which require collective action in public spaces. Neither did the Court demand transparency about the technologies used by the police force, which is often shielded behind the ‘trade secrets’ by the corporations who produce them, nor did the Court act to prevent fragmentation and inconsistency between local police forces’ rules and regulations on automated facial recognition technology, which leaves the law less predictable. Thus, while the Bridges decision is reassuring and demands change in the discretionary approaches of UK police in the short term, its long-term impact in burning bridges between the expanding public space surveillance infrastructure and the modern state is less certain.

Le tecnologie di riconoscimento facciale consentono di identificare una persona a partire dall’immagine del volto. Grazie alla combinazione di tecniche biometriche e procedimenti algoritmici, queste tecnologie offrono potenzialità uniche a beneficio di autorità pubbliche e soggetti privati. Tramite esse – basti pensare – è possibile risalire alle generalità e alle caratteristiche di una persona che si trova a grande distanza o in movimento, a prescindere da qualsiasi volontà cooperativa. L’impiego di questi strumenti è sempre più diffuso e pervasivo, per finalità quali la repressione di illeciti, la garanzia della sicurezza, l’erogazione di servizi, o per motivi economici e commerciali.
Queste tecnologie, allo stesso tempo, aprono a nuove forme di sorveglianza di massa; conferiscono un potere inedito di tracciamento, di profilazione e di controllo sulle persone; possono originare insidiosi fenomeni di discriminazione. Non è un caso che numerosi Stati, istituzioni come l’Unione Europea e il Consiglio d’Europa, o le stesse imprese private stiano discutendo su una possibile moratoria all’impiego di questi strumenti per determinati scopi.
Nel quadro di queste sfide, il presente Volume intende aprire una nuova riflessione sulle tecnologie di riconoscimento facciale nella prospettiva del diritto costituzionale. L’analisi, in particolare, si pone l’obiettivo di esplorare la capacità di questi sistemi tecnologici di incidere trasversalmente su una pluralità di libertà e di diritti fondamentali, a scapito dei singoli o di interi gruppi sociali. L’indagine vuole offrire un contributo per comprendere le potenzialità, i limiti e i possibili sviluppi della normativa giuridica attualmente vigente, allo scopo di verificare in che termini il diritto possa porre un argine efficace contro questa capacità invasiva e consentire così di beneficiare a pieno di questi strumenti. Con ciò, i legislatori nazionali ed europei sono chiamati ad uno sforzo di ripensamento tanto delle tecniche quanto dei contenuti della regolazione, soprattutto per riconfigurare le modalità di tutela stessa di alcuni diritti fondamentali e la disciplina di tecnologie innovative come quelle in discussione.

There are plenty of softwares that can detect human facial movements and relate them to a definite emotional expression. In its first part, the paper investigates how this can be done, what are the variations and the interpretations of eyebrow movements. In the second part, the possibility of artificial intelligence being able to recognise such human emotions is discussed.

With this Thesis, I problematize the intellectual historiography behind keyword coding–or key-wording–for facial expressions of emotion, emotion-based, and emotions-like phenomena in the German socio-cultural media imaginary. Using digital research techniques to perform a federated query that links word-organized archival content, I depart from the new Media Art Research Thesaurus to comparatively analyse keyword-coded information resources–or “artworks”–on the online Graphic Art Collection of Göttweig Abbey and the Archive of Digital Art: Johann Nepomuk Strixner’s 1808-1815 Master Study of Albrecht Dürer’s The Four Apostles, and Julius von Bismarck, Benjamin Maus, and Richard Whelmer’s 2008, 2010, and 2014 Public Face. By this meta-analysis I will prove how, in this our Algorithmic Age, that to ask the “face question” calls for a digital literacy in the “black box” keyword concepts by which the artistic, scientific, and technological cultural sectors today operationalize facial expressions into universal as well as utilitarian attributes, and code individual expressors into typologies. I pose that these keyword metadata function along with image-resources to “turn real lives into writing” for the computation, datafication, and even commodification of the facial expression of emotion. But I also propose that such keyword metadata have, since at least the Age of Print, functioned as an “auxiliary organ” or technological prosthesis for extending naked or natural perception of our own faces as well as the faces of others, and thereby overcome the limitations of our own emotional intelligence.

A brief discussion of some of the crucial elements of art comprehension and creation. While primarily pertaining to comics per se, I try to be philosophically comprehensive and holistic both in terms of subject matter as well as life in general.

Originally posted at my blog: http://elysiumisnow.weebly.com/

The London Riots of August 2011 were notable for the prominence of CCTV images of offenders in news and social media, as well as in investigation, prosecution and conviction. The Metropolitan Police Service relied on specialist units that had in fact been established in the five years prior to the riots, which had been tasked with acting systematically upon CCTV image evidence: a procedural approach deemed so effective it had been termed the ‘Third Forensics’. This article discusses the significance of this claim and its implications for the justice system. The use of images in the investigations of the riots was highly effective, suggesting claims for substantially improved impact in investigation and prosecution are valid, and earlier scepticism regarding both utility and surveillance society agendas in public area CCTV studies was justified. Systematic procedural use of CCTV footage is not new, however, as demonstrated following riots in Vancouver, Canada, and earlier in Bradford, UK. Furthermore, identification in the ‘Third Forensics’ is eyewitness recognition, not scientifically or technologically comparable to fingerprints or DNA. The article suggests this difference affects risks of prejudice and miscarriages of justice, and the ‘profiling’ of individuals and social categories images appear to represent. The article concludes that while forensic investigation of CCTV images may not meet scientific criteria of a third forensic discipline, it does define a nascent development in police investigation where improvements in procedure have combined with proliferating CCTV systems and social media. This has led to a novel set of circumstances, which raises a number of unexplored issues of such significance that ‘Third Forensics’ is a suitable term to use to define them.

Join Sgt. Brendan Gill of the Prince George’s County PD Joint Analysis Intelligence Center, Robert Harrell of Veritone, and Lt. Frank Borelli of Officer.com to learn how to harness your department’s case evidence and booking database to identify suspect leads faster, accelerate case clearance rates and save money with AI. Topics included Challenges in Identifying Suspects in Video and Image Evidence; Suspect Identification, Best Practices from Prince George’s Police Department; Harnessing the Power of Your Booking Database to Identify Suspect Leads Faster; and a demonstration of Veritone IDentify.

A detailed analysis of all the available evidence in the matter of the alleged death of Jesse Woodson James in St Joseph, Missouri, April 3, 1882. As well as a review of the 1995 exhumation in Kearney, Missouri, the J. Frank Dalton exhumation in May 2000 and the Jere Miah James exhumation in Neodesha, Kansas in May, 2004.

La conformité des usages de la technologie de reconnaissance faciale au droit à la vie privée est fonction de ces critères techniques (authentification v. identification notamment), mais aussi des juges appelés à l’évaluer. La présente contribution évalue la conformité des déploiement à l'état de droit français et européen. Si la jurisprudence constitutionnelle française apparaît une digue fragile au développement de la surveillance – ciblée, comme de masse – (I), celle des cours européennes offre, à défaut d’un obstacle insurmontable, la perspective de solides limites à cette évolution (II).

Publication parue au Dalloz IP/IT / 309 / Juin 2021.

Previous research on emotion recognition of Twitter users centered on the use of lexicons and basic classifiers on pack of words models, despite the recent accomplishments of deep learning in many disciplines of natural language processing. The study's main question is if deep learning can help them improve their performance. Because of the scant contextual information that most posts offer, emotion analysis is still difficult. The suggested method can capture more emotion sematic than existing models by projecting emoticons and words into emoticon space, which improves the performance of emotion analysis. In a microblog setting, this aids in the detection of subjectivity, polarity, and emotion. It accomplishes this by utilizing hash tags to create three large emotion-labeled data sets that can be compared to various emotional orders. Then compare the results of a few words and character-based repetitive and convolutional neural networks to the results of a pack of words and latent semantic indexing models. Furthermore, the specifics examine the transferability of the most recent hidden state representations across distinct emotional classes and whether it is possible to construct a unified model for predicting each of them using a common representation. It's been shown that repetitive neural systems, especially character-based ones, outperform pack-of-words and latent semantic indexing models. The semantics of the token must be considered while classifying the tweet emotion. The semantics of the tokens recorded in the hash map may be simply searched. Despite these models' low exchange capacities, the recently presented training heuristic produces a unity model with execution comparable to the three solo models.

Résumé exécutif en français du rapport réalisé au nom de l'Agenda urbain pour la Commission européenne intitulé "New Surveillance Technologies in Public Spaces Challenges and Perspectives for European Law at the Example of Facial Recognition"