The human face recognition is a research field which raised a great amount of interest of
related disciplines. Because of its high efficiency and accuracy, it has been applied in vivid …

Background and Aims Publicly available databases containing colonoscopic imaging data
are valuable resources for artificial intelligence (AI) research. Currently, little is known …

With the help of the adaptive gain control algorithm and the flocking SWARM algorithm with
adversarial agents, the project described in this article makes the entire system …

Self-supervised learning (SSL) has led to important breakthroughs in computer vision by
allowing learning from large amounts of unlabeled data. As such, it might have a pivotal role …

This paper focuses on the improvement of a left and right hand tracker based on
convolutional neural networks that we previously studied using computer vision related …

As the number of urban vehicles surges, issues like traffic accidents and air pollution are
becoming increasingly severe. To address these challenges, this paper presents a computer …

Detecting colorectal polyps promptly and accurately is crucial in preventing the progression
of colorectal cancer. These polyps cause severe conditions in the colon or rectum …

Random splitting strategy is a common approach for training, testing, and validating object
detection algorithms based on deep learning. Is common for datasets to have images …

Computer-aided polyp detection (CADe) is becoming a standard, integral part of any
modern colonoscopy system. A typical colonoscopy CADe detects a polyp in a single frame …

The operation of distribution networks is currently facing potential safety and quality defects
that pose significant hazards. One solution to strengthen management, reduce manual …