ACM Computing Surveys

Multimodal Artificial Intelligence (Multimodal AI), in general, involves various types of data (e.g., images, texts, or data collected from different sensors), feature engineering (e.g., extraction, combination/fusion), and decision-making (e.g., majority ...

Time Series Classification and Extrinsic Regression are important and challenging machine learning tasks. Deep learning has revolutionized natural language processing and computer vision and holds great promise in other fields such as time series analysis ...

Security is an increasing concern for real-time systems (RTS). Over the last decade or so, researchers have demonstrated attacks and defenses aimed at such systems. In this article, we identify, classify and measure the effectiveness of the security ...

While AI algorithms have shown remarkable success in various fields, their lack of transparency hinders their application to real-life tasks. Although explanations targeted at non-experts are necessary for user trust and human-AI collaboration, the ...

Financial Sentiment Analysis (FSA) is an important domain application of sentiment analysis that has gained increasing attention in the past decade. FSA research falls into two main streams. The first stream focuses on defining tasks and developing ...

Muscle fatigue represents a complex physiological and psychological phenomenon that impairs physical performance and increases the risks of injury. It is important to continuously monitor fatigue levels for early detection and management of fatigue. The ...

Fuzzing is a very effective testing methodology to find bugs. In a nutshell, a fuzzer sends many slightly malformed messages to the software under test, hoping for crashes or incorrect system behaviour. The methodology is relatively simple, although ...

In this survey, we provide a comprehensive review of more than 200 articles, technical reports, and GitHub repositories published over the last 10 years on the recent developments of deep learning techniques for iris recognition, covering broad topics on ...

The widespread adoption and success of Machine Learning (ML) technologies depend on thorough testing of the resilience and robustness to adversarial attacks. The testing should focus on both the model and the data. It is necessary to build robust and ...

Video coding that pursues the highest compression efficiency is the art of computing for rate-distortion optimization. The optimization has been approached in different ways, exemplified by two typical frameworks: block-based hybrid video coding and end-...

Respiratory illness diagnosis and continuous monitoring are becoming popular as sensitive markers of chronic diseases. This interest has motivated the increased development of respiratory illness diagnosis by exploiting wireless communication as a sensing ...

The rapid growth of the internet has reached the fourth generation, i.e., web 4.0, which supports Sentiment Analysis (SA) in many applications such as social media, marketing, risk management, healthcare, businesses, websites, data mining, e-learning, ...

Designing and generating new data under targeted properties has been attracting various critical applications such as molecule design, image editing and speech synthesis. Traditional hand-crafted approaches heavily rely on expertise experience and ...

Due to low numbers of qubits and their error-proneness, Noisy Intermediate-Scale Quantum (NISQ) computers impose constraints on the size of quantum algorithms they can successfully execute. State-of-the-art research introduces various techniques ...

Text Generation aims to produce plausible and readable text in human language from input data. The resurgence of deep learning has greatly advanced this field, in particular, with the help of neural generation models based on pre-trained language models (...

Context: Information Technology organizations are aiming to implement DevOps capabilities to fulfill market, customer, and internal needs. While many are successful with DevOps implementation, others still have difficulty measuring DevOps success in their ...

As the use of deep learning techniques has grown across various fields over the past decade, complaints about the opaqueness of the black-box models have increased, resulting in an increased focus on transparency in deep learning models. This work ...

Novel technological swarm and industry 4.0 mold the recent Robot vision research into innovative discovery. To enhance technological paradigm Deep Learning offers remarkable pace to move towards diversified advancement. This research considers the most ...

The development of the Internet of Things (IoT) paradigm and its significant spread as an affordable data source has brought many challenges when pursuing efficient data collection, distribution, and storage. Since such hierarchical logical architecture ...

This tutorial presents a novel search system—the Attractor-Based Search System (ABSS)—that can solve the Traveling Salesman Problem very efficiently with optimality guarantee. From the perspective of dynamical systems, a heuristic local search algorithm ...

Smartphones can unobtrusively capture human behavior and contextual data such as user interaction and mobility. Thus far, smartphone sensor data have primarily been used to gain behavioral insights through correlation analysis. This article provides a ...

When developing XR applications for Industry 4.0, it is important to consider the integration of visual displays, hardware components, and multimodal interaction techniques that are compatible with the entire system. The potential use of multimodal ...

Intel Trust Domain Extensions (TDX) is an architectural extension in the 4th Generation Intel Xeon Scalable Processor that supports confidential computing. TDX allows the deployment of virtual machines in the Secure-Arbitration Mode (SEAM) with encrypted ...

Question-answering systems are recognized as popular and frequently effective means of information seeking on the web. In such systems, information seekers can receive a concise response to their queries by presenting their questions in natural language. ...

Due to underlying privacy-sensitive information in user-item interaction data, the risk of privacy leakage exists in the centralized-training recommender system (RecSys). To this issue, federated learning, a privacy-oriented distributed computing paradigm,...

Computational approach to politeness is the task of automatically predicting and/or generating politeness in text. This is a pivotal task for conversational analysis, given the ubiquity and challenges of politeness in interactions. The computational ...

Blockchain has attracted significant attention in recent years due to its potential to revolutionize various industries by providing trustlessness. To comprehensively examine blockchain systems, this article presents both a macro-level overview on the ...