23 citations · 33 across the 8 of their papers we have counts for
8 papers
Temporal Feature Distillation for Label-Efficient Precise Event Spotting in Sports Videos
Hao Xu, Xinyu Wei, Sam Wells +1
Precise Event Spotting (PES) requires distinguishing visually similar yet semantically distinct adjacent frames, making it fundamentally different from image classification and coa…
DMS2F-HAD: A Dual-branch Mamba-based Spatial-Spectral Fusion Network for Hyperspectral Anomaly Detection
Aayushma Pant, Lakpa Tamang, Tsz-Kwan Lee +1
Hyperspectral anomaly detection (HAD) aims to identify rare and irregular targets in high-dimensional hyperspectral images (HSIs), which are often noisy and unlabelled data. Existi…
TOTNet: Occlusion-Aware Temporal Tracking for Robust Ball Detection in Sports Videos
Hao Xu, Arbind Agrahari Baniya, Sam Wells +3
Robust ball tracking under occlusion remains a key challenge in sports video analysis, affecting tasks like event detection and officiating. We present TOTNet, a Temporal Occlusion…
Hyperspectral Anomaly Detection Methods: A Survey and Comparative Study
Aayushma Pant, Arbind Agrahari Baniya, Tsz-Kwan Lee +1
Hyperspectral images are high-dimensional datasets comprising hundreds of contiguous spectral bands, enabling detailed analysis of materials and surfaces. Hyperspectral anomaly det…
A Survey of Deep Learning Video Super-Resolution
Arbind Agrahari Baniya, Tsz-Kwan Lee, Peter Eklund +1
Video super-resolution (VSR) is a prominent research topic in low-level computer vision, where deep learning technologies have played a significant role. The rapid progress in deep…
Unmasking Gender Bias in Recommendation Systems and Enhancing Category-Aware Fairness
Tahsin Alamgir Kheya, Mohamed Reda Bouadjenek, Sunil Aryal
Recommendation systems are now an integral part of our daily lives. We rely on them for tasks such as discovering new movies, finding friends on social media, and connecting job se…
Enabling clustering algorithms to detect clusters of varying densities through scale-invariant data preprocessing
Sunil Aryal, Jonathan R. Wells, Arbind Agrahari Baniya +1
In this paper, we show that preprocessing data using a variant of rank transformation called 'Average Rank over an Ensemble of Sub-samples (ARES)' makes clustering algorithms robus…
A Novel Data Pre-processing Technique: Making Data Mining Robust to Different Units and Scales of Measurement
Arbind Agrahari Baniya, Sunil Aryal, Santosh KC
Many existing data mining algorithms use feature values directly in their model, making them sensitive to units/scales used to measure/represent data. Pre-processing of data based…