35 citations · 72 across the 25 of their papers we have counts for
9 papers · 1 filter
EarthDial: Turning Multi-sensory Earth Observations to Interactive Dialogues
Sagar Soni, Akshay Dudhane, Hiyam Debary +8
Automated analysis of vast Earth observation data via interactive Vision-Language Models (VLMs) can unlock new opportunities for environmental monitoring, disaster response, and {r…
CLIP meets DINO for Tuning Zero-Shot Classifier using Unlabeled Image Collections
Mohamed Fazli Imam, Rufael Fedaku Marew, Jameel Hassan +3
In the era of foundation models, CLIP has emerged as a powerful tool for aligning text & visual modalities into a common embedding space. However, the alignment objective used to t…
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…
Improving 3D Medical Image Segmentation at Boundary Regions using Local Self-attention and Global Volume Mixing
Daniya Najiha Abdul Kareem, Mustansar Fiaz, Noa Novershtern +2
Volumetric medical image segmentation is a fundamental problem in medical image analysis where the objective is to accurately classify a given 3D volumetric medical image with voxe…
A Survey of the Self Supervised Learning Mechanisms for Vision Transformers
Asifullah Khan, Anabia Sohail, Mustansar Fiaz +11
Advances in deep learning are re-defining how visual data is processed and understand by the machines. Vision Transformers (ViTs) have recently demonstrated prominent performance i…
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…
Medical Image Segmentation Using Directional Window Attention
Daniya Najiha Abdul Kareem, Mustansar Fiaz, Noa Novershtern +1
Accurate segmentation of medical images is crucial for diagnostic purposes, including cell segmentation, tumor identification, and organ localization. Traditional convolutional neu…
ChangeBind: A Hybrid Change Encoder for Remote Sensing Change Detection
Mubashir Noman, Mustansar Fiaz, Hisham Cholakkal
Change detection (CD) is a fundamental task in remote sensing (RS) which aims to detect the semantic changes between the same geographical regions at different time stamps. Existin…
ELGC-Net: Efficient Local-Global Context Aggregation for Remote Sensing Change Detection
Mubashir Noman, Mustansar Fiaz, Hisham Cholakkal +2
Deep learning has shown remarkable success in remote sensing change detection (CD), aiming to identify semantic change regions between co-registered satellite image pairs acquired…