Apellai
A subsonic client, built using Kotlin, for storing, filtering, searching music libraries and podcasts in servers, with additional options for like/dislike, media controls and server switching.
A subsonic client, built using Kotlin, for storing, filtering, searching music libraries and podcasts in servers, with additional options for like/dislike, media controls and server switching.
Built with MERN stack, a web application for managing the residence and meal system for hostels, with separate interfaces for tenants and owners.
A Flutter application for tracking progress of forming new habits and visualising over defined periods of time, with additional features of priority-based task scheduling.
Preprint, 2024
In this paper, we utilise the FFT-ReLU prior to enhance relevant frequency components using the Fast Fourier Transform (FFT) while applying ReLU sparsity to suppress noise. Our approach utilizes a Vision Transformer as a pre-processing model to generate a less blurry intermediate image by capturing both local and global features, which is then refined through FFT-ReLU, resulting in a sharp, high-quality output. Our experimental results demonstrate that our method consistently outperforms state-of-the-art image deblurring models, providing sharper and more visually compelling images.
IEEE/CVF Winter Conference on Applications of Computer Vision, 2025
The paper introduces a method for blind image deblurring, which is the process of recovering a sharp image from a blurred one without prior knowledge about the blur kernel. The proposed method leverages a prior that targets the blur kernel to achieve effective deblurring across a wide range of image types. The authors' extensive empirical analysis shows that their algorithm achieves results that are competitive with the state-of-the-art blind image deblurring algorithms, and it offers up to two times faster inference, making it a highly efficient solution.
Recommended citation: Abdul Mohaimen Al Radi, Prothito Shovon Majumder, & Md. Mosaddek Khan. (2024). Blind Image Deblurring with FFT-ReLU Sparsity Prior.
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Under review, 2025
We introduce the largest real-world image deblurring dataset constructed from smartphone slow-motion videos. Using 240 frames captured over one second, we simulate realistic long-exposure blur by averaging frames to produce blurry images, while using the temporally centered frame as the sharp reference. Our dataset contains over 42,000 high-resolution blur-sharp image pairs, making it approximately 10 times larger than widely used datasets, with 8 times the amount of different scenes, including indoor and outdoor environments, with varying object and camera motions. We benchmark multiple state-of-the-art (SOTA) deblurring models on our dataset and observe significant performance degradation, highlighting the complexity and diversity of our benchmark. Our dataset serves as a challenging new benchmark to facilitate robust and generalizable deblurring models.
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Undergraduate Course, CSE Department, BRAC University, 2024
This course introduces the concepts of the fundamental data structures of computer science, such as
Undergraduate Course, CSE Department, BRAC University, 2025
This course digs deep into analysing time and space complexities of algorithms, and introduces some classic algorithms of computer science involving
Undergraduate Course, CSE Department, BRAC University, 2025
This is a foundational course for introducing mathematical concepts for building the basics of problem-solving. The course discusses
Undergraduate Course, CSE Department, BRAC University, 2025
This course discusses the layers of the OSI model and the TCP/IP protocol suite, and discusses different functionalities and mathematical notions of the physical and data link layers. Topics include