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• Adaptive Vision-Language Prompt Learners for Learning with Noisy Labels
• Continual Evidential Deep Learning for Out-of-Distribution Detection
• ROBO STEAM – INCLUSIVE TECHNOLOGIES
• Bayesian DivideMix++forEnhancedLearningwithNoisyLabels
• Behavioural patterns discovery for lifestyle analysis from egocentric
  photo-streams
• CCLM: Class-Conditional Label Noise
  Modelling
• CEDL+: Exploiting evidential deep learning for continual out-of-distribution
  detection
• CLIP-DoRA:Weight-decomposedLow-rankAdaptationfor
  EfficientVision-LanguageModels
• Decodingclassdynamicsinlearningwithnoisylabels
• Deepensemble-basedhardsampleminingforfoodrecognition
• Dual Polarity Prompts with Stochastic
  Entropy Perturbation for Label Noise
• Efficient Deep Learning Ensemble for Skin Lesion Classification
• Enriching Unbounded Appearances
  for Neural Radiance Fields
• All4One: Symbiotic Neighbour Contrastive Learning
  via Self-Attention and Redundancy Reduction
• Good Fences Make Good Neighbours
• FoodMem: Near real-time and precise food video segmentation
• LLM-Generated Semantic Co-occurrences
  for Multi-label Food Recognition
• LOFI: LOng-tailed FIne-Grained Network for Food Recognition
• Multi-Task Visual Food Recognition by Integrating an Ontology Supported with LLM
• Ontology-Driven Deep Learning Model for Multitask Visual Food
  Analysis
• Precision at scale: Domain-specific datasets on-demand
• Time-aware Circulant Matrices for
  Question-based Temporal Localization
• VolE++: A Text-Guided Point-Cloud
  Framework for Food 3D Reconstruction
  and Volume Estimation
• VolTex: Food Volume Estimation using Text-Guided Segmentation and Neural
  Surface Reconstruction