The health care sector is totally different from any other industry. It is a high priority sector
and consumers expect the highest level of care and services regardless of cost. The health …

Deep learning has emerged as a leading machine learning tool in object detection and has
attracted attention with its achievements in progressing medical image analysis …

This paper investigates a deep learning method in image classification for the detection of
colorectal cancer with ResNet architecture. The exceptional performance of a deep learning …

More than 90% of colorectal cancer is gradually transformed from colorectal polyps. In
clinical practice, precise polyp segmentation provides important information in the early …

Convolutional neural networks, are one of the most representative deep learning models.
CNNs were extensively used in many aspects of medical image analysis, allowing for great …

Camouflaged object detection (COD) aims to identify the objects that conceal themselves in
natural scenes. Accurate COD suffers from a number of challenges associated with low …

Training a deep convolutional neural network (CNN) from scratch is difficult because it
requires a large amount of labeled training data and a great deal of expertise to ensure …

This paper presents the culmination of our research in designing a system for computer-
aided detection (CAD) of polyps in colonoscopy videos. Our system is based on a hybrid …

Ensemble models achieve high accuracy by combining a number of base estimators and
can increase the reliability of machine learning compared to a single estimator. Additionally …

Gaps in colonoscopy skills among endoscopists, primarily due to experience, have been
identified, and solutions are critically needed. Hence, the development of a real-time robust …