3 papers
cs.CV2026
Ordinal Adaptive Correction: A Data-Centric Approach to Ordinal Image Classification with Noisy Labels
Alireza Sedighi Moghaddam, Mohammad Reza Mohammadi
Labeled data is a fundamental component in training supervised deep learning models for computer vision tasks. However, the labeling process, especially for ordinal image classific…
cs.LG2025
A prototype-based model for set classification
Mohammad Mohammadi, Sreejita Ghosh
Classification of sets of inputs (e.g., images and texts) is an active area of research within both computer vision (CV) and natural language processing (NLP). A common way to repr…
cs.CV2025
Feature Based Methods in Domain Adaptation for Object Detection: A Review Paper
Helia Mohamadi, Mohammad Ali Keyvanrad, Mohammad Reza Mohammadi
Domain adaptation, a pivotal branch of transfer learning, aims to enhance the performance of machine learning models when deployed in target domains with distinct data distribution…