A5031094197- COVID-19 diagnosis using AI
- AI in cancer detection
- Radiomics and Machine Learning in Medical Imaging
- Colorectal Cancer Screening and Detection
- Advanced Neural Network Applications
- Tuberculosis Research and Epidemiology
- Advanced Image and Video Retrieval Techniques
- Machine Learning in Healthcare
- Robotics and Sensor-Based Localization
- 3D Shape Modeling and Analysis
- Lung Cancer Diagnosis and Treatment
- Human Pose and Action Recognition
- Video Surveillance and Tracking Methods
- Anomaly Detection Techniques and Applications
Vietnam National University Ho Chi Minh City
2022-2024
Ho Chi Minh City University of Science
2023-2024
Medical image segmentation is the technique that helps doctor view and has a precise diagnosis, partic-ularly in Colorectal Cancer. Specifically, with increase cases, diagnosis identification need to be faster more accurate for many patients; endoscopic images, task been vital helping identify position of polyps or ache system correctly. As result, efforts have made apply deep learning automate polyp segmentation, mostly ameliorate U -shape structure. However, simple skip connection scheme...
Chest radiography is a common medical diagnostic procedure, often resulting in long-tailed distribution of clinical findings. This challenges standard deep learning methods, which tend to favor more classes and might miss less frequent but equally important "tail" classes. X-ray diagnoses represent multi-label problem due the potential for multiple simultaneous diseases patients. In this paper, we propose straightforward yet highly effective techniques address imbalance chest datasets. We...
Recent advancements in ReID systems have primarily focused on individuals and four-wheeled vehicles to meet the rising demand for public safety traffic management. However, domain of motorcycle has mainly been overlooked despite its significance security applications. Extracting features from both motorcycles their riders poses a unique challenge. In this paper, we present AANet, an innovative deep-learning model designed explicitly ReID. AANet incorporates multi-atrous convolution...
Polyp segmentation has recently garnered significant attention, and multiple methods have been formulated to achieve commendable outcomes. However, these techniques often confront difficulty when working with the complex polyp foreground their surrounding regions because of nature convolution operation. Besides, most existing forget exploit potential information from decoder stages. To address this challenge, we suggest combining MetaFormer, introduced as a baseline for integrating CNN...
Colonoscopy is widely acknowledged as the most efficient screening method for detecting colorectal cancer and its early stages, such polyps. However, procedure faces challenges with high miss rates due to heterogeneity of polyps dependence on individual observers. Therefore, several deep learning systems have been proposed considering criticality polyp detection segmentation in clinical practices. While existing approaches shown advancements their results, they still possess important...
Many real-world image recognition problems, such as diagnostic medical imaging exams, are "long-tailed" $\unicode{x2013}$ there a few common findings followed by many more relatively rare conditions. In chest radiography, diagnosis is both long-tailed and multi-label problem, patients often present with multiple simultaneously. While researchers have begun to study the problem of learning in recognition, studied interaction label imbalance co-occurrence posed long-tailed, disease...
The retrieval of 3D objects has gained significant importance in recent years due to its broad range applications computer vision, graphics, virtual reality, and augmented reality. However, the presents challenges intricate nature models, which can vary shape, size, texture, have numerous polygons vertices. To this end, we introduce a novel SHREC challenge track that focuses on retrieving relevant animal models from dataset using sketch queries expedites accessing through available sketches....