GitHub

TFM Dataset & Benchmark: Automated Tear Film Break-Up Analysis

Classification (TF-Cls) 'Clear', 'Closed', 'Broken', 'Blur' 6,247 3632 × 2760 4,687:561:999(75%:9%:16%) Object Detection (TF-Det) Inside, Middle, Outside Rings 4,736 ...
Frontiers

Advancing standardized cattle behavior classification with a random forest model evaluated across diverse datasets

The lack of precise, autonomous tools for monitoring and classifying cattle behavior limits farmers’ ability to make proactive and informed decisions regarding grazing and herd management. Currently, ...
Microsoft

Multi-Label Classification for Colon Cancer Using Histopathological Images

Colon cancer classification has a significant guidance value in clinical diagnoses and medical prognoses. The classification of colon cancers with high accuracy is the premise of efficient treatment.
Frontiers

VAE deep learning model with domain adaptation, transfer learning and harmonization for diagnostic classification from multi-site neuroimaging data

The acquisition sites include: CALTECH, California Institute of Technology; CMU, Carnegie Mellon University; KKI, Kennedy Krieger Institute; LEUVEN, University of Leuven; MAX, Ludwig Maximilians ...
IEEE

Label-Aware Hierarchical Ranking Model for Multi-Label Text Classification

Abstract: Multi-label text classification involves assigning multiple relevant categories to a single text, enabling applications in academic indexing, medical diagnostics, and e-commerce. However, ...
BioSpace

Alterity Therapeutics Reports Positive Topline Data from Open-Label Phase 2 Clinical Trial of ATH434 in Multiple System Atrophy

– Data are Consistent with Phase 2 Double-Blind Trial and Support Advancement of ATH434 in MSA – MELBOURNE, Australia and SAN FRANCISCO, July 28, 2025 (GLOBE NEWSWIRE) -- Alterity Therapeutics (ASX: ...
GitHub

Pull requests: 75ade/Multi-label-classification-using-arXiv-dataset-wtih-deep-learning

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.