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20232026
most citedMulti-Task Learning Approach for Unified Biometric Estimation from Fetal Ultrasound Anomaly Scans

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cs.CV2026

Projected Gradient Unlearning for Text-to-Image Diffusion Models: Defending Against Concept Revival Attacks

Aljalila Aladawi, Mohammed Talha Alam, Fakhri Karray

Machine unlearning for text-to-image diffusion models aims to selectively remove undesirable concepts from pre-trained models without costly retraining. Current unlearning methods…

cs.CV2025

AdaptPrompt: Parameter-Efficient Adaptation of VLMs for Generalizable Deepfake Detection

Yichen Jiang, Mohammed Talha Alam, Sohail Ahmed Khan +2

Detectors of AI-generated images tend to inherit the biases of the data they are trained on: models fitted to GAN imagery learn to treat GAN-specific artifacts as the very definiti…

cs.CV2025

FaceAnonyMixer: Cancelable Faces via Identity Consistent Latent Space Mixing

Mohammed Talha Alam, Fahad Shamshad, Fakhri Karray +1

Advancements in face recognition (FR) technologies have amplified privacy concerns, necessitating methods that protect identity while maintaining recognition utility. Existing face…

cs.CV2025

ADAM-Dehaze: Adaptive Density-Aware Multi-Stage Dehazing for Improved Object Detection in Foggy Conditions

Fatmah AlHindaassi, Mohammed Talha Alam, Fakhri Karray

Adverse weather conditions, particularly fog, pose a significant challenge to autonomous vehicles, surveillance systems, and other safety-critical applications by severely degradin…

cs.CV2024

Introducing SDICE: An Index for Assessing Diversity of Synthetic Medical Datasets

Mohammed Talha Alam, Raza Imam, Mohammad Areeb Qazi +2

Advancements in generative modeling are pushing the state-of-the-art in synthetic medical image generation. These synthetic images can serve as an effective data augmentation metho…

cs.CV2024

AstroSpy: On detecting Fake Images in Astronomy via Joint Image-Spectral Representations

Mohammed Talha Alam, Raza Imam, Mohsen Guizani +1

The prevalence of AI-generated imagery has raised concerns about the authenticity of astronomical images, especially with advanced text-to-image models like Stable Diffusion produc…

cs.CV2024

CosmoCLIP: Generalizing Large Vision-Language Models for Astronomical Imaging

Raza Imam, Mohammed Talha Alam, Umaima Rahman +2

Existing vision-text contrastive learning models enhance representation transferability and support zero-shot prediction by matching paired image and caption embeddings while pushi…

cs.CV2024

FLARE up your data: Diffusion-based Augmentation Method in Astronomical Imaging

Mohammed Talha Alam, Raza Imam, Mohsen Guizani +1

The intersection of Astronomy and AI encounters significant challenges related to issues such as noisy backgrounds, lower resolution (LR), and the intricate process of filtering an…