7 papers · 1 filter
Waste-Bench: A Comprehensive Benchmark for Evaluating VLLMs in Cluttered Environments
Muhammad Ali, Salman Khan
Recent advancements in Large Language Models (LLMs) have paved the way for Vision Large Language Models (VLLMs) capable of performing a wide range of visual understanding tasks. Wh…
COSNet: A Novel Semantic Segmentation Network using Enhanced Boundaries in Cluttered Scenes
Muhammad Ali, Mamoona Javaid, Mubashir Noman +2
Automated waste recycling aims to efficiently separate the recyclable objects from the waste by employing vision-based systems. However, the presence of varying shaped objects havi…
CBAM-SwinT-BL: Small Rail Surface Defect Detection Method Based on Swin Transformer with Block Level CBAM Enhancement
Jiayi Zhao, Alison Wun-lam Yeung, Ali Muhammad +2
Under high-intensity rail operations, rail tracks endure considerable stresses resulting in various defects such as corrugation and spellings. Failure to effectively detect defects…
Assessment of Spectral based Solutions for the Detection of Floating Marine Debris
Muhammad Alì, Francesca Razzano, Sergio Vitale +4
Typically, the detection of marine debris relies on in-situ campaigns that are characterized by huge human effort and limited spatial coverage. Following the need of a rapid soluti…
Underwater Object Detection Enhancement via Channel Stabilization
Muhammad Ali, Salman Khan
The complex marine environment exacerbates the challenges of object detection manifold. Marine trash endangers the aquatic ecosystem, presenting a persistent challenge. Accurate de…
FANet: Feature Amplification Network for Semantic Segmentation in Cluttered Background
Muhammad Ali, Mamoona Javaid, Mubashir Noman +2
Existing deep learning approaches leave out the semantic cues that are crucial in semantic segmentation present in complex scenarios including cluttered backgrounds and translucent…