35 citations · 72 across the 25 of their papers we have counts for
23 papers · 1 filter
Towards Effective Waste Segmentation for Automated Waste Recycling in Cluttered Background
Mamoona Javaid, Mubashir Noman, Abdul Hannan +3
Rapid expansion of urban areas and population growth is causing an immense increase in waste production, which demands the need for efficient and automated waste management. In thi…
EoCD: Encoder only Remote Sensing Change Detection
Mubashir Noman, Mustansar Fiaz, Hiyam Debary +4
Being a cornerstone of temporal analysis, change detection has been playing a pivotal role in modern earth observation. Existing change detection methods rely on the Siamese encode…
OpenEarthAgent: A Unified Framework for Tool-Augmented Geospatial Agents
Akashah Shabbir, Muhammad Umer Sheikh, Muhammad Akhtar Munir +8
Recent progress in multimodal reasoning has enabled agents that interpret imagery, connect it with language, and execute structured analytical tasks. Extending these capabilities t…
GeoVLM-R1: Reinforcement Fine-Tuning for Improved Remote Sensing Reasoning
Mustansar Fiaz, Hiyam Debary, Paolo Fraccaro +4
Recent advances in reinforcement learning (RL) have delivered strong reasoning capabilities in natural image domains, yet their potential for Earth Observation (EO) remains largely…
PrediTree: A Multi-Temporal Sub-meter Dataset of Multi-Spectral Imagery Aligned With Canopy Height Maps
Hiyam Debary, Mustansar Fiaz, Levente Klein
We present PrediTree, the first comprehensive open-source dataset designed for training and evaluating tree height prediction models at sub-meter resolution. This dataset combines…
HyRet-Change: A hybrid retentive network for remote sensing change detection
Mustansar Fiaz, Mubashir Noman, Hiyam Debary +2
Recently convolution and transformer-based change detection (CD) methods provide promising performance. However, it remains unclear how the local and global dependencies interact t…
InceptionMamba: Efficient Multi-Stage Feature Enhancement with Selective State Space Model for Microscopic Medical Image Segmentation
Daniya Najiha Abdul Kareem, Abdul Hannan, Mubashir Noman +3
Accurate microscopic medical image segmentation plays a crucial role in diagnosing various cancerous cells and identifying tumors. Driven by advancements in deep learning, convolut…
Open-Set Semi-Supervised Learning for Long-Tailed Medical Datasets
Daniya Najiha A. Kareem, Jean Lahoud, Mustansar Fiaz +2
Many practical medical imaging scenarios include categories that are under-represented but still crucial. The relevance of image recognition models to real-world applications lies…
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…
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…
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…
DDAM-PS: Diligent Domain Adaptive Mixer for Person Search
Mohammed Khaleed Almansoori, Mustansar Fiaz, Hisham Cholakkal
Person search (PS) is a challenging computer vision problem where the objective is to achieve joint optimization for pedestrian detection and re-identification (ReID). Although pre…
SA2-Net: Scale-aware Attention Network for Microscopic Image Segmentation
Mustansar Fiaz, Moein Heidari, Rao Muhammad Anwer +1
Microscopic image segmentation is a challenging task, wherein the objective is to assign semantic labels to each pixel in a given microscopic image. While convolutional neural netw…
Remote Sensing Change Detection With Transformers Trained from Scratch
Mubashir Noman, Mustansar Fiaz, Hisham Cholakkal +4
Current transformer-based change detection (CD) approaches either employ a pre-trained model trained on large-scale image classification ImageNet dataset or rely on first pre-train…
PS-ARM: An End-to-End Attention-aware Relation Mixer Network for Person Search
Mustansar Fiaz, Hisham Cholakkal, Sanath Narayan +2
Person search is a challenging problem with various real-world applications, that aims at joint person detection and re-identification of a query person from uncropped gallery imag…
Brain MRI Segmentation using Rule-Based Hybrid Approach
Mustansar Fiaz, Kamran Ali, Abdul Rehman +2
Medical image segmentation being a substantial component of image processing plays a significant role to analyze gross anatomy, to locate an infirmity and to plan the surgical proc…
Handcrafted and Deep Trackers: Recent Visual Object Tracking Approaches and Trends
Mustansar Fiaz, Arif Mahmood, Sajid Javed +1
In recent years visual object tracking has become a very active research area. An increasing number of tracking algorithms are being proposed each year. It is because tracking has…
Tracking Noisy Targets: A Review of Recent Object Tracking Approaches
Mustansar Fiaz, Arif Mahmood, Soon Ki Jung
Visual object tracking is an important computer vision problem with numerous real-world applications including human-computer interaction, autonomous vehicles, robotics, motion-bas…
Comparative Study of ECO and CFNet Trackers in Noisy Environment
Mustansar Fiaz, Sajid Javed, Arif Mahmood +1
Object tracking is one of the most challenging task and has secured significant attention of computer vision researchers in the past two decades. Recent deep learning based tracker…