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Garbage management is exceptionally critical and poses enormous environmental challenges. It has always been a vital issue in municipal corporations. However, municipal agencies have developed and used garbage management systems. Garbage ...

Low‐light object detection is needed for ensuring security, enabling surveillance, and enhancing safety in diverse applications, including autonomous vehicles, surveillance systems, and search and rescue operations. A comprehensive study on low‐...

Recently, emergence has received widespread attention from the research community along with the success of large-scale models. Different from the literature, we hypothesize a key factor that promotes the performance during the increase of scale: the ...

This work explores techniques and metrics applied to the process of population synthesis used in activity-based modeling for traffic and transport simulation. The paper presents a novel population synthesis approach based on applying artificial neural ...

Magnetic Resonance Imaging (MRI) based Autism Spectrum Disorder (ASD) detection approaches face various challenges due to variations in brain connectivity patterns, limited sample sizes, and heterogeneity of available data. These challenges make ...

Brain-computer interfaces (BCIs) offer a novel method of converting brain activity into valuable data. This study investigates the use of electroencephalogram (EEG) signals for recognizing brainwave signals to record human thoughts. Our research focuses ...

Parkinson's disease (PD) is a chronic neurodegenerative disease. Motor symptoms are very mild in the early stages, making diagnosis difficult. Recent studies have shown that the use of patient voice recordings can aid in early diagnosis. Although the ...

Intrusion detection is a cyber‐security method that is significant for network security. It is utilized to detect behaviors that compromise security and privacy within a network or in the context of a computer system. To enhance the ...

The Retrieval Augmented Language Model, which is a model that combines a language model and a database, has various advantages from having knowledge in the form of a database and has been actively studied, especially in the Question Answering task. Since ...

How to represent a human face pattern? While it is presented in a continuous way in human visual system, computers often store and process it in a discrete manner with 2D arrays of pixels. The authors attempt to learn a continuous surface ...

With the introduction of more recent deep learning models such as encoder‐decoder, text generation frameworks have gained a lot of popularity. In Natural Language Generation (NLG), controlling the information and style of the output produced is ...

The supply chains of the Canadian forest products industry are largely dependent on accurate demand forecasts. The USA is the major export market for the Canadian forest products industry, although some Canadian provinces are also exporting forest ...

RNA molecules play critical roles in various biological processes, which are predominantly governed by their secondary and tertiary structures. The secondary structure of RNA helps us understand the functional behaviours and regulatory mechanisms of the ...

This paper established a novel approach for developing simplified yet accurate models using artificial neural networks (ANNs) in industrial environments. It demonstrates that combining nonlinear regression with neural network modeling enhances predictive ...

Video games are becoming a part of the lives of many, many people. They are able to evoke a wide range of emotions, from joy and excitement to fear and empathy, creating deep immersion and memorable impressions for players. How do they manage it ...

Mathematical modeling of many natural and physical phenomena in industry, engineering sciences and basic sciences lead to linear and non-linear devices. In many cases, the coefficients of these devices, taking into account qualitative or linguistic ...

In this work, a novel technique to train machine learning models is introduced, which is based on digital simulations of certain types of quantum systems. This represents a drastic departure from the standard approach of quantum machine learning ...

Loss function of a training phase obtained by means of the quantum inspired machine learning approach suggested in this paper. image image

A Deep Harmonic Decomposition (Deep HarDec) approach is proposed in this paper, being developed by means of a deep neural network, allowing to obtain estimations of the amplitude and phase quantities of a given periodic signal. Consequently, ...

This work is devoted to methods for creating fast and accurate neural network algorithms for central processors, which were proposed by scientists of the V.L. Arlazarov’s scientific school. It outlines general principles and approaches to ...

This article is devoted to the history of development and main research areas of the scientific school in the field of pattern recognition, image processing and analysis, and artificial intelligence and machine learning, founded in the early 1990s ...