IEEE

Tip-Adapter-SA: Training-Free CLIP-Adapter Enhanced by Semantic Alignment for Multi-Label Few-Shot Classification with Single Positive Labels

Abstract: Multi-label classification is a fundamental task that requires predicting all applicable labels for each sample. Previous methods often rely heavily on training models with large-scale multi ...
IEEE

Federated Chain Context Optimization for Long-Tailed Multi-Label Image Classification

Abstract: Federated learning is an emerging machine learning paradigm that effectively alleviates the data silo problem by distributing the model training process to multiple data holders. However, ...
TMCnet

WiMi Releases Next-Generation Hybrid Quantum Neural Network Structure Technology, Breaking Through the Bottleneck of Image Multi-Classification

BEIJING, Dec. 22, 2025 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, launched a hybrid ...
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

From scales to circuits: integrating behavioral diagnosis and neural biomarkers for improved classification in disorders of consciousness

Introduction: In this study, we propose a data-driven approach that integrates behavioral diagnosis with neuroimaging features to identify representative UWS and MCS patients from a large inpatient ...