J. Biomed. Inform. 2026 – Multimodal AI in healthcare: Review of vision-language foundation models for real-world medical applications
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J. Biomed. Inform. 2026 – Multimodal AI in healthcare: Review of vision-language foundation models for real-world medical applications

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Taha Razzaq, Murtaza Taj, Asim Iqbal Abstract: \initial{T}\textbf{he emergence of foundation models has marked a transformative shift in AI, enabling robust generalization across diverse downstream tasks through putative zero-shot learning. Large Language Models and Vision-Language Models have demonstrated strong capabilities in tasks such as image interpretation, report generation, and question answering by effectively learning from…

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JMP2024 – An exploratory deep learning approach to investigate tuberculosis pathogenesis in nonhuman primate model

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Faisal Yaseen, Murtaza Taj, Resmi Ravindran, Fareed Zaffar, Paul A. Luciw, Aamer Ikram, Saerah Iffat Zafar, Tariq Gill, Michael Hogarth and Imran H. Khan Abstract: Background Tuberculosis (TB) kills approximately 1.6 million people yearly despite the fact anti-TB drugs are generally curative. Therefore, TB-case detection and monitoring of therapy, need a comprehensive approach. Automated radiological…

IEEETGRS2024 – Stereollax Net: Stereo Parallax Based Deep Learning Network For Building Height Estimation
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IEEETGRS2024 – Stereollax Net: Stereo Parallax Based Deep Learning Network For Building Height Estimation

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Sana Jabbar and Murtaza Taj Abstract: Accurate estimation of building heights is crucial for effective urban planning and resource management as it provides essential geometric information about the urban landscape. Many end-to-end deep learning-based networks have been proposed for image-to-height mapping using high-resolution nonoptical and optical remote sensing imagery. In this study, we develop a…

IEEEJSTAR2020 – Kiln-Net: A gated neural network for detection of brick kilns in South Asia
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IEEEJSTAR2020 – Kiln-Net: A gated neural network for detection of brick kilns in South Asia

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Usman Nazir, Usman Khalid Mian, Muhammad Usman Sohail, Murtaza Taj and Momin Uppal Abstract: The availability of high-resolution satellite imagery has enabled several new applications. One such application is identification of brick kilns for the elimination of modern day slavery which is also one of UN’s Sustainable Development Goals (SDG). This requires automated analysis of…

IEEE TGRS – A Residual-Dyad Encoder Discriminator Network for Remote Sensing Image Matching
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IEEE TGRS – A Residual-Dyad Encoder Discriminator Network for Remote Sensing Image Matching

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Numan Khurshid, Mohbat Tharani, Murtaza Taj, and Faisal Qureshi Abstract: We propose a new method for remote sensing image matching. The proposed method uses encoder subnetwork of an autoencoder pre-trained on GTCrossView data to construct image features. A discriminator network trained on University of California Merced Land Use/Land Cover dataset (LandUse) and High-resolution Satellite Scene…

NCA2021 – Statistically Correlated Multi-task Learning for Autonomous Driving
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NCA2021 – Statistically Correlated Multi-task Learning for Autonomous Driving

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Waseem Abbas, M. Fakhir Khan, Murtaza Taj, and Arif Mahmood Abstract Autonomous driving research is an emerging domain in computer vision and machine learning areas. Most existing methods perform Single Task Learning (STL) from one or more images while Multi-Task Learning (MTL) is more efficient due to the leverage of shared information between different tasks….

ToG 2012 – Bilinear Spatiotemporal Basis Models
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ToG 2012 – Bilinear Spatiotemporal Basis Models

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Our paper in ACM Transactions on Graphics April 2012 presents a fundamentally new way to model time-varying point clouds, that dramatically reduces processing times for common graphics pipeline tasks such as labeling, gap-filling, denoising, and motion touch-up. This is joint work with Carnegie Mellon University and Disney Research Pittsburgh, and has been presented at Siggraph 2012.

TIP 2012 – Correlation Coefficient Based Fast Template Matching Through Partial Elimination
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TIP 2012 – Correlation Coefficient Based Fast Template Matching Through Partial Elimination

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Arif Mahmood, Sohaib Khan IEEE Transactions on Image Processing, Vol 21, No 4, April 2012 Abstract Partial computation elimination techniques are often used for fast template matching. At a particular search location, computations are prematurely terminated as soon as it is found that this location cannot compete already known best-match location. Due to non-monotonic growth…

TPAMI 2011 – Trajectory Space: A Dual Representation for Nonrigid Structure from Motion
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TPAMI 2011 – Trajectory Space: A Dual Representation for Nonrigid Structure from Motion

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Ijaz Akhter, Yaser Sheikh, Sohaib Khan, Takeo Kanade IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol 33, No 7, Jul 2011 Abstract Existing approaches to nonrigid structure from motion assume that the instantaneous 3D shape of a deforming object is a linear combination of basis shapes. These basis are object dependent and therefore have…

SPM 2011 – Distributed and Decentralized Multi-Camera Tracking: A Survey
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SPM 2011 – Distributed and Decentralized Multi-Camera Tracking: A Survey

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Murtaza Taj, Andrea Cavallaro IEEE Signal Processing Magazine, 2011 Abstract In recent years the decreasing cost of cameras and advances in miniaturization have favoured the deployment of largescale camera networks. This growing number of cameras enables new signal processing applications that use cooperatively multiple sensors over wide areas. In particular, object tracking is an important…