most citedPSMamba: Progressive Self-supervised Vision Mamba for Plant Disease Recognition

2 citations · 3 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Probing Diffusion Denoising Dynamics for Contrastive Representation Learning

Yasong Dai, Zeeshan Hayder, David Ahmedt-Aristizabal +1

Text-to-image diffusion models exhibit unprecedented generative capability and contain rich intermediate representations that can be useful for discriminative vision tasks. Motivat…

cs.CV20252 cited

PSMamba: Progressive Self-supervised Vision Mamba for Plant Disease Recognition

Abdullah Al Mamun, Miaohua Zhang, David Ahmedt-Aristizabal +2

Self-supervised Learning (SSL) has become a powerful paradigm for representation learning without manual annotations. However, most existing frameworks focus on global alignment an…

cs.CV2025

Quality-Driven and Diversity-Aware Sample Expansion for Robust Marine Obstacle Segmentation

Miaohua Zhang, Mohammad Ali Armin, Xuesong Li +5

Marine obstacle detection demands robust segmentation under challenging conditions, such as sun glitter, fog, and rapidly changing wave patterns. These factors degrade image qualit…

cs.CV20251 cited

StateSpace-SSL: Linear-Time Self-supervised Learning for Plant Disease Detection

Abdullah Al Mamun, Miaohua Zhang, David Ahmedt-Aristizabal +2

Self-supervised learning (SSL) is attractive for plant disease detection as it can exploit large collections of unlabeled leaf images, yet most existing SSL methods are built on CN…

cs.CV2025

ConMamba: Contrastive Vision Mamba for Plant Disease Detection

Abdullah Al Mamun, Miaohua Zhang, David Ahmedt-Aristizabal +2

Plant Disease Detection (PDD) is a key aspect of precision agriculture. However, existing deep learning methods often rely on extensively annotated datasets, which are time-consumi…