5 citations · 6 across the 3 of their papers we have counts for
4 papers · 1 filter
Transductive Decoupled Variational Inference for Few-Shot Classification
Anuj Singh, Hadi Jamali-Rad
The versatility to learn from a handful of samples is the hallmark of human intelligence. Few-shot learning is an endeavour to transcend this capability down to machines. Inspired…
Self-Supervised Class-Cognizant Few-Shot Classification
Ojas Kishore Shirekar, Hadi Jamali-Rad
Unsupervised learning is argued to be the dark matter of human intelligence. To build in this direction, this paper focuses on unsupervised learning from an abundance of unlabeled…
Tilted Cross Entropy (TCE): Promoting Fairness in Semantic Segmentation
Attila Szabo, Hadi Jamali-Rad, Siva-Datta Mannava
Traditional empirical risk minimization (ERM) for semantic segmentation can disproportionately advantage or disadvantage certain target classes in favor of an (unfair but) improved…
Lookahead Adversarial Learning for Near Real-Time Semantic Segmentation
Hadi Jamali-Rad, Attila Szabo
Semantic segmentation is one of the most fundamental problems in computer vision with significant impact on a wide variety of applications. Adversarial learning is shown to be an e…