Generalized video anomaly event detection: Systematic taxonomy and comparison of deep models

Y Liu, D Yang, Y Wang, J Liu, J Liu… - ACM Computing …, 2024 - dl.acm.org
Video Anomaly Detection (VAD) serves as a pivotal technology in the intelligent surveillance
systems, enabling the temporal or spatial identification of anomalous events within videos …

Application of artificial intelligence to gastroenterology and hepatology

C Le Berre, WJ Sandborn, S Aridhi, MD Devignes… - Gastroenterology, 2020 - Elsevier
Since 2010, substantial progress has been made in artificial intelligence (AI) and its
application to medicine. AI is explored in gastroenterology for endoscopic analysis of …

[HTML][HTML] Application of convolutional neural networks for automated ulcer detection in wireless capsule endoscopy images

H Alaskar, A Hussain, N Al-Aseem, P Liatsis… - Sensors, 2019 - mdpi.com
Detection of abnormalities in wireless capsule endoscopy (WCE) images is a challenging
task. Typically, these images suffer from low contrast, complex background, variations in …

Polyp detection during colonoscopy using a regression-based convolutional neural network with a tracker

R Zhang, Y Zheng, CCY Poon, D Shen, JYW Lau - Pattern recognition, 2018 - Elsevier
A computer-aided detection (CAD) tool for locating and detecting polyps can help reduce the
chance of missing polyps during colonoscopy. Nevertheless, state-of-the-art algorithms were …

Fusion of color histogram and LBP-based features for texture image retrieval and classification

P Liu, JM Guo, K Chamnongthai, H Prasetyo - Information Sciences, 2017 - Elsevier
Abstract The Local Binary Pattern (LBP) operator and its variants play an important role as
the image feature extractor in the textural image retrieval and classification. The LBP-based …

Dilated CNN for abnormality detection in wireless capsule endoscopy images

N Goel, S Kaur, D Gunjan, SJ Mahapatra - Soft Computing, 2022 - Springer
Wireless capsule endoscopy is a non-invasive and painless procedure to examine the
gastrointestinal tract of human body, and an experienced clinician takes 2–3 hours for …

Multi-scale context-guided deep network for automated lesion segmentation with endoscopy images of gastrointestinal tract

S Wang, Y Cong, H Zhu, X Chen, L Qu… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
Accurate lesion segmentation based on endoscopy images is a fundamental task for the
automated diagnosis of gastrointestinal tract (GI Tract) diseases. Previous studies usually …

Investigating the significance of color space for abnormality detection in wireless capsule endoscopy images

N Goel, S Kaur, D Gunjan, SJ Mahapatra - Biomedical Signal Processing …, 2022 - Elsevier
Abstract Wireless Capsule Endoscopy is a non-invasive and painless procedure to examine
the gastrointestinal tract of human body. An experienced clinician takes 2-3 h for a complete …

A survey on contemporary computer-aided tumor, polyp, and ulcer detection methods in wireless capsule endoscopy imaging

T Rahim, MA Usman, SY Shin - Computerized Medical Imaging and …, 2020 - Elsevier
Wireless capsule endoscopy (WCE) is a process in which a patient swallows a camera-
embedded pill-shaped device that passes through the gastrointestinal (GI) tract, captures …

Generic feature learning for wireless capsule endoscopy analysis

S Seguí, M Drozdzal, G Pascual, P Radeva… - Computers in biology …, 2016 - Elsevier
The interpretation and analysis of wireless capsule endoscopy (WCE) recordings is a
complex task which requires sophisticated computer aided decision (CAD) systems to help …