output
20022026
most citedCalibration of Moving Puncture Simulations

392 citations

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7 papers · 1 filter

cs.CV20251 cited

Feature Coding for Scalable Machine Vision

Md Eimran Hossain Eimon, Juan Merlos, Ashan Perera +3

Deep neural networks (DNNs) drive modern machine vision but are challenging to deploy on edge devices due to high compute demands. Traditional approaches-running the full model on-…

cs.CV20251 cited

ROI-Packing: Efficient Region-Based Compression for Machine Vision

Md Eimran Hossain Eimon, Alena Krause, Ashan Perera +4

This paper introduces ROI-Packing, an efficient image compression method tailored specifically for machine vision. By prioritizing regions of interest (ROI) critical to end-task ac…

cs.CV20252 cited

Efficient Feature Compression for Machines with Global Statistics Preservation

Md Eimran Hossain Eimon, Hyomin Choi, Fabien Racapé +4

The split-inference paradigm divides an artificial intelligence (AI) model into two parts. This necessitates the transfer of intermediate feature data between the two halves. Here,…

cs.CV20256 cited

Enabling Next-Generation Consumer Experience with Feature Coding for Machines

Md Eimran Hossain Eimon, Juan Merlos, Ashan Perera +3

As consumer devices become increasingly intelligent and interconnected, efficient data transfer solutions for machine tasks have become essential. This paper presents an overview o…

cs.CV2024

Research Experience of an Undergraduate Student in Computer Vision and Robotics

Ayush V. Gowda, Juan D. Yepes, Daniel Raviv

This paper focuses on the educational journey of a computer engineering undergraduate student venturing into the domain of computer vision and robotics. It explores how optical flo…

cs.CV201912 cited

Improving Borderline Adulthood Facial Age Estimation through Ensemble Learning

Felix Anda, David Lillis, Aikaterini Kanta +4

Achieving high performance for facial age estimation with subjects in the borderline between adulthood and non-adulthood has always been a challenge. Several studies have used diff…