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20212026
most citedDeep learning universal crater detection using Segment Anything Model (SAM)

14 citations · 18 across the 16 of their papers we have counts for

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cs.CV2026

HiAP: A Multi-Granular Stochastic Auto-Pruning Framework for Vision Transformers

Andy Li, Aiden Durrant, Milan Markovic +1

Vision Transformers require significant computational resources and memory bandwidth, severely limiting their deployment on resource-constraint hardware. Most structured pruning me…

cs.CV2025

Getting the Numbers Right$\unicode{x2014}$Modelling Multi-Class Object Counting in Dense and Varied Scenes

Villanelle O'Reilly, Jonathan Cox, Georgios Leontidis +3

Density map estimation enables accurate object counting in heavily occluded, and densely packed scenes where detection-based counting fails. In multi-class density estimation, clas…

cs.CV2025

EquiCaps: Predictor-Free Pose-Aware Pre-Trained Capsule Networks

Athinoulla Konstantinou, Georgios Leontidis, Mamatha Thota +1

Learning self-supervised representations that are invariant and equivariant to transformations is crucial for advancing beyond traditional visual classification tasks. However, man…

cs.CV2024

Pushing the Limits of Sparsity: A Bag of Tricks for Extreme Pruning

Andy Li, Aiden Durrant, Milan Markovic +5

Pruning of deep neural networks has been an effective technique for reducing model size while preserving most of the performance of dense networks, crucial for deploying models on…

cs.CV2024

Capsule Network Projectors are Equivariant and Invariant Learners

Miles Everett, Aiden Durrant, Mingjun Zhong +1

Learning invariant representations has been the long-standing approach to self-supervised learning. However, recently progress has been made in preserving equivariant properties in…

cs.CV2024

LeOCLR: Leveraging Original Images for Contrastive Learning of Visual Representations

Mohammad Alkhalefi, Georgios Leontidis, Mingjun Zhong

Contrastive instance discrimination methods outperform supervised learning in downstream tasks such as image classification and object detection. However, these methods rely heavil…