1 citations · 1 across the 5 of their papers we have counts for
5 papers
Characterizing Learning in Deep Neural Networks using Tractable Algorithmic Complexity Analysis
Pedram Bakhtiarifard, Sophia N. Wilson, Mahmoud Afifi +2
Training large-scale deep neural networks (DNNs) is resource-intensive, making model compression a practical necessity. The widely accepted ''learning as compression'' hypothesis p…
Color Matching Using Hypernetwork-Based Kolmogorov-Arnold Networks
Artem Nikonorov, Georgy Perevozchikov, Andrei Korepanov +4
We present cmKAN, a versatile framework for color matching. Given an input image with colors from a source color distribution, our method effectively and accurately maps these colo…
Small Contributions, Small Networks: Efficient Neural Network Pruning Based on Relative Importance
Mostafa Hussien, Mahmoud Afifi, Kim Khoa Nguyen +1
Recent advancements have scaled neural networks to unprecedented sizes, achieving remarkable performance across a wide range of tasks. However, deploying these large-scale models o…
What Do You See? Enhancing Zero-Shot Image Classification with Multimodal Large Language Models
Abdelrahman Abdelhamed, Mahmoud Afifi, Alec Go
Large language models (LLMs) have been effectively used for many computer vision tasks, including image classification. In this paper, we present a simple yet effective approach fo…
Rawformer: Unpaired Raw-to-Raw Translation for Learnable Camera ISPs
Georgy Perevozchikov, Nancy Mehta, Mahmoud Afifi +1
Modern smartphone camera quality heavily relies on the image signal processor (ISP) to enhance captured raw images, utilizing carefully designed modules to produce final output ima…