Latest AI and machine learning research in medical ethics / professional responsibility for healthcare professionals.
Three-dimensional electron microscopy (3D EM) enables the quantitative analysis of cellular ultrastr...
Accurate segmentation of neuronal cells in fluorescence microscopy is a fundamental task for quantit...
The global impact of COVID-19 has caused a significant rise in the demand for psychological counseli...
This study aims to develop a novel multi-modal fusion framework for brain tumor segmentation that ...
Floods are among the most frequent natural hazards and cause significant social and economic damag...
Out-of-Distribution (OoD) segmentation is critical for safety-sensitive applications like autonomo...
Out-of-Distribution (OoD) segmentation is critical for safety-sensitive applications like autonomo...
Edge detection (ED) remains a fundamental task in computer vision, yet its performance is often hi...
Building on our previous work introducing Fredholm Neural Networks (Fredholm NNs/ FNNs) for solvin...
Medical AI diagnosis including histopathology segmentation has derived benefits from the recent de...
Assisting medical students with clinical reasoning (CR) during clinical scenario training remains ...
Background and objective: Medical image segmentation is a core task in various clinical applicatio...
Small- and medium-sized manufacturers need innovative data tools but, because of competition and p...
Remote sensing semantic segmentation must address both what the ground objects are within an image...
Polyp segmentation in colonoscopy images is crucial for early detection and diagnosis of colorecta...
Selecting relevant features is an important and necessary step for intelligent machines to maximiz...
Oriented object detection has been crucial for rotation-sensitive tasks and has garnered significant...
Medical image segmentation is a pivotal task within the realms of medical image analysis and compute...
3D anomaly detection aims to solve the problem that image anomaly detection is greatly affected by l...
The application of machine learning methods to the groundwater pollution inversion problem has becom...
The use of Natural Language Processing (NLP) in highstakes AI-based applications has increased sig...