5 citations · 12 across the 25 of their papers we have counts for
27 papers
AgriScope: Pixel-Grounded Multimodal Understanding for Agricultural Images
Abderrahmene Boudiaf, Mohamad Alanssari, Irfan Hussain +1
Agricultural image understanding requires fine-grained recognition of plant diseases, pests, crop structures, and botanical species under complex real-world conditions. Despite rec…
CheXGround: Anatomical Region Tokens for Grounded Longitudinal Chest X-ray Interpretation
Adonay Demewez Gebremedhin, Wessam Shehieb, Sara Alansari +4
Recent radiology multi-modal language models have made substantial progress in chest X-ray report generation, visual question answering, and temporal reasoning. While longitudinal…
Uncertainty-Aware Decision Making in Multimodal Large Language Models
Abderrahmene Boudiaf, Irfan Hussain, Sajid Javed
Multimodal large language models (MLLMs) increasingly answer questions whose correctness depends on visual, textual, temporal, acoustic, document, chart, or embodied evidence. Thei…
From Multi-Resolution Cells to Gigapixel Whole Slide Images Foundation Model for Computational Pathology
Basit Alawode, Moshira Ali Abdalla, Dwarikanath Mahapatra +2
Vision Transformers (ViTs) and their hierarchical variants have achieved strong performance in Computational Pathology (CPath). However, most are pre-trained on single-resolution W…
SENTRY: SAM2-Enhanced Neighbor-Aware and Temporally Reasoned Memory for Visual Tracking
Mohamad Alansari, Yonathan Michael, Hasan AlMarzouqi +3
We revisit the memory update mechanism in SAM2-based visual object tracking and identify confidence-only mask selection as the dominant cause of drift under occlusion, rapid motion…
SegRAG: Retrieval Augmented Spatial Prompting for Open Vocabulary Semantic Segmentation
Abderrahmene Boudiaf, Irfan Hussain, Sajid Javed
Frozen segmentation foundation models often fail when the target class appears in a form that is weakly represented during pretraining. To address this problem, we introduce SegRAG…
MLLM-HWSI: A Multimodal Large Language Model for Hierarchical Whole Slide Image Understanding
Basit Alawode, Arif Mahmood, Muaz Khalifa Al-Radi +6
Whole Slide Images (WSIs) exhibit hierarchical structure, where diagnostic information emerges from cellular morphology, regional tissue organization, and global context. Existing…
AgriChat: A Multimodal Large Language Model for Agriculture Image Understanding
Abderrahmene Boudiaf, Irfan Hussain, Sajid Javed
The deployment of Multimodal Large Language Models (MLLMs) in agriculture is currently stalled by a critical trade-off: the existing literature lacks the large-scale agricultural d…
SPARROW: Learning Spatial Precision and Temporal Referential Consistency in Pixel-Grounded Video MLLMs
Mohamad Alansari, Naufal Suryanto, Divya Velayudhan +3
Multimodal large language models (MLLMs) have advanced from image-level reasoning to pixel-level grounding, but extending these capabilities to videos remains challenging as models…
MUOT_3M: A 3 Million Frame Multimodal Underwater Benchmark and the MUTrack Tracking Method
Ahsan Baidar Bakht, Mohamad Alansari, Muhayy Ud Din +5
Underwater Object Tracking (UOT) is crucial for efficient marine robotics, large scale ecological monitoring, and ocean exploration; however, progress has been hindered by the scar…
Rethinking Memory Design in SAM-Based Visual Object Tracking
Mohamad Alansari, Muzammal Naseer, Hasan Al Marzouqi +2
\noindent Memory has become the central mechanism enabling robust visual object tracking in modern segmentation-based frameworks. Recent methods built upon Segment Anything Model 2…
Cytoplasmic Strings Analysis in Human Embryo Time-Lapse Videos using Deep Learning Framework
Anabia Sohail, Mohamad Alansari, Ahmed Abughali +8
Infertility is a major global health issue, and while in-vitro fertilization has improved treatment outcomes, embryo selection remains a critical bottleneck. Time-lapse imaging ena…
Spatio-Temporal State Space Model For Efficient Event-Based Optical Flow
Muhammad Ahmed Humais, Xiaoqian Huang, Hussain Sajwani +2
Event cameras unlock new frontiers that were previously unthinkable with standard frame-based cameras. One notable example is low-latency motion estimation (optical flow), which is…
CLDTracker: A Comprehensive Language Description for Visual Tracking
Mohamad Alansari, Sajid Javed, Iyyakutti Iyappan Ganapathi +2
VOT remains a fundamental yet challenging task in computer vision due to dynamic appearance changes, occlusions, and background clutter. Traditional trackers, relying primarily on…
Multi-Resolution Pathology-Language Pre-training Model with Text-Guided Visual Representation
Shahad Albastaki, Anabia Sohail, Iyyakutti Iyappan Ganapathi +6
In Computational Pathology (CPath), the introduction of Vision-Language Models (VLMs) has opened new avenues for research, focusing primarily on aligning image-text pairs at a sing…
snnTrans-DHZ: A Lightweight Spiking Neural Network Architecture for Underwater Image Dehazing
Vidya Sudevan, Fakhreddine Zayer, Rizwana Kausar +4
Underwater image dehazing is critical for vision-based marine operations because light scattering and absorption can severely reduce visibility. This paper introduces snnTrans-DHZ,…
Underwater Image Enhancement by Convolutional Spiking Neural Networks
Vidya Sudevan, Fakhreddine Zayer, Rizwana Kausar +4
Underwater image enhancement (UIE) is fundamental for marine applications, including autonomous vision-based navigation. Deep learning methods using convolutional neural networks (…
AquaticCLIP: A Vision-Language Foundation Model for Underwater Scene Analysis
Basit Alawode, Iyyakutti Iyappan Ganapathi, Sajid Javed +3
The preservation of aquatic biodiversity is critical in mitigating the effects of climate change. Aquatic scene understanding plays a pivotal role in aiding marine scientists in th…
Anomaly Detection for Industrial Applications, Its Challenges, Solutions, and Future Directions: A Review
Abdelrahman Alzarooni, Ehtesham Iqbal, Samee Ullah Khan +3
Anomaly detection from images captured using camera sensors is one of the mainstream applications at the industrial level. Particularly, it maintains the quality and optimizes the…
Dehazing-aided Multi-Rate Multi-Modal Pose Estimation Framework for Mitigating Visual Disturbances in Extreme Underwater Domain
Vidya Sudevan, Fakhreddine Zayer, Taimur Hassan +4
This paper delves into the potential of DU-VIO, a dehazing-aided hybrid multi-rate multi-modal Visual-Inertial Odometry (VIO) estimation framework, designed to thrive in the challe…
Hybrid-Neuromorphic Approach for Underwater Robotics Applications: A Conceptual Framework
Vidya Sudevan, Fakhreddine Zayer, Sajid Javed +3
This paper introduces the concept of employing neuromorphic methodologies for task-oriented underwater robotics applications. In contrast to the increasing computational demands of…
Advancing Histopathology with Deep Learning Under Data Scarcity: A Decade in Review
Ahmad Obeid, Said Boumaraf, Anabia Sohail +5
Recent years witnessed remarkable progress in computational histopathology, largely fueled by deep learning. This brought the clinical adoption of deep learning-based tools within…
Video Anomaly Detection in 10 Years: A Survey and Outlook
Moshira Abdalla, Sajid Javed, Muaz Al Radi +2
Video anomaly detection (VAD) holds immense importance across diverse domains such as surveillance, healthcare, and environmental monitoring. While numerous surveys focus on conven…
CPLIP: Zero-Shot Learning for Histopathology with Comprehensive Vision-Language Alignment
Sajid Javed, Arif Mahmood, Iyyakutti Iyappan Ganapathi +3
This paper proposes Comprehensive Pathology Language Image Pre-training (CPLIP), a new unsupervised technique designed to enhance the alignment of images and text in histopathology…