A convolutional neural network (CNN) is one of the most significant networks in the deep
learning field. Since CNN made impressive achievements in many areas, including but not …

Autonomous vehicles have become a topic of interest in recent times due to the rapid
advancement of automobile and computer vision technology. The ability of autonomous …

Pattern recognition and feature extraction of images always have been important subjects in
improving the performance of image classification and Content-Based Image Retrieval …

With the growing trend in autonomous vehicles, accurate recognition of traffic signs has
become crucial. This research focuses on the use of convolutional neural networks for traffic …

Multi-object tracking in video surveillance is subjected to illumination variation, blurring,
motion, and similarity variations during the identification process in real-world practice. The …

Teaching and exam proctoring represent key pillars of the education system. Human
proctoring, which involves visually monitoring examinees throughout exams, is an important …

Determining the cyclic-alternating-pattern (CAP) phases in sleep using
electroencephalography (EEG) signals is crucial for assessing sleep quality. However, most …

Cautionary traffic signs are of immense significance to traffic safety. In this study, a robust
and optimal real‐time approach to recognize the Indian cautionary traffic signs (ICTS) is …

For safety decisions in social media applications, it is necessary to classify personification
patterns. The paper proposes using video material to apply machine learning to select, and …

In this paper, we introduce HoughToRadon Transform layer, a novel layer designed to
improve the speed of neural networks incorporated with Hough Transform to solve semantic …