activity
20222025
most citedOptimized Approaches to Malware Detection: A Study of Machine Learning and Deep Learning Techniques

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV2025

A Modified VGG19-Based Framework for Accurate and Interpretable Real-Time Bone Fracture Detection

Md. Ehsanul Haque, Abrar Fahim, Shamik Dey +4

Early and accurate detection of the bone fracture is paramount to initiating treatment as early as possible and avoiding any delay in patient treatment and outcomes. Interpretation…

cs.CR2025★ 2 cited

Optimized Approaches to Malware Detection: A Study of Machine Learning and Deep Learning Techniques

Abrar Fahim, Shamik Dey, Md. Nurul Absur +3

Digital systems find it challenging to keep up with cybersecurity threats. The daily emergence of more than 560,000 new malware strains poses significant hazards to the digital eco…

cs.LG2024

Exploring Curriculum Learning for Vision-Language Tasks: A Study on Small-Scale Multimodal Training

Rohan Saha, Abrar Fahim, Alona Fyshe +1

For specialized domains, there is often not a wealth of data with which to train large machine learning models. In such limited data / compute settings, various methods exist aimin…

cs.CV2024

It's Not a Modality Gap: Characterizing and Addressing the Contrastive Gap

Abrar Fahim, Alex Murphy, Alona Fyshe

Multi-modal contrastive models such as CLIP achieve state-of-the-art performance in zero-shot classification by embedding input images and texts on a joint representational space.…

cs.LG2022★ 1 cited

Unsupervised Space Partitioning for Nearest Neighbor Search

Abrar Fahim, Mohammed Eunus Ali, Muhammad Aamir Cheema

Approximate Nearest Neighbor Search (ANNS) in high dimensional spaces is crucial for many real-life applications (e.g., e-commerce, web, multimedia, etc.) dealing with an abundance…