3 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.CV2024★ 1 cited
Towards Optimal Feature-Shaping Methods for Out-of-Distribution Detection
Qinyu Zhao, Ming Xu, Kartik Gupta +3
Feature shaping refers to a family of methods that exhibit state-of-the-art performance for out-of-distribution (OOD) detection. These approaches manipulate the feature representat…
cs.CV2023★ 3 cited
Reducing the Side-Effects of Oscillations in Training of Quantized YOLO Networks
Kartik Gupta, Akshay Asthana
Quantized networks use less computational and memory resources and are suitable for deployment on edge devices. While quantization-aware training QAT is the well-studied approach t…
cs.CV2023
Efficient Labelling of Affective Video Datasets via Few-Shot & Multi-Task Contrastive Learning
Ravikiran Parameshwara, Ibrahim Radwan, Akshay Asthana +3
Whilst deep learning techniques have achieved excellent emotion prediction, they still require large amounts of labelled training data, which are (a) onerous and tedious to compile…