2 citations · 4 across the 5 of their papers we have counts for
7 papers
PATTS: Parallel-Aware Test-Time Scaling for Thought-Image Generation in Multimodal Discrete Diffusion LLMs
Yasong Dai, Zeeshan Hayder, David Ahmedt-Aristizabal +1
Test-time scaling (TTS) improves generative models by allocating additional inference-time computation to sampling, search, and verification. Existing image generation approaches,…
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…
BiFM: Bidirectional Flow Matching for Few-Step Image Editing and Generation
Yasong Dai, Zeeshan Hayder, David Ahmedt-Aristizabal +1
Recent diffusion and flow matching models have demonstrated strong capabilities in image generation and editing by progressively removing noise through iterative sampling. While th…
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…
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…
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…
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…