Amir Erfan Eshratifar

Yahoo (United States) — United States

Computer Science · Physical Sciences

7h-index209citations24works1.32yr avg
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Research Topics

Advanced Neural Network Applications(14), IoT and Edge/Fog Computing(10), Domain Adaptation and Few-Shot Learning(7), Advanced Memory and Neural Computing(3), Advanced Image and Video Retrieval Techniques(3)

Publications24 total

SCOT: Self-Supervised Contrastive Pretraining for Zero-Shot Compositional Retrieval
2025
SCOT: Self-Supervised Contrastive Pretraining For Zero-Shot Compositional Retrieval
arXiv (Cornell University)·2025Open Access
Salient Object-Aware Background Generation using Text-Guided Diffusion Models
2024· 5 cited
Salient Object-Aware Background Generation using Text-Guided Diffusion Models
arXiv (Cornell University)·2024Open Access
Coarse2Fine: a two-stage training method for fine-grained visual classification
Machine Vision and Applications·2021· 2 citedOpen Access
Runtime Deep Model Multiplexing for Reduced Latency and Energy Consumption Inference
2020· 1 citedOpen Access
Video Person Re-ID: Fantastic Techniques and Where to Find Them (Student Abstract)
Proceedings of the AAAI Conference on Artificial Intelligence·2020· 14 citedOpen Access
Efficient Training of Deep Convolutional Neural Networks by Augmentation in Embedding Space
2020Open Access
Efficient Training of Deep Convolutional Neural Networks by Augmentation\n in Embedding Space
arXiv (Cornell University)·2020Open Access
Run-time Deep Model Multiplexing
2020· 2 cited
Runtime Deep Model Multiplexing for Reduced Latency and Energy\n Consumption Inference
arXiv (Cornell University)·2020Open Access
Video Person Re-ID: Fantastic Techniques and Where to Find Them
arXiv (Cornell University)·2019· 7 citedOpen Access
JointDNN: An Efficient Training and Inference Engine for Intelligent Mobile Cloud Computing Services
IEEE Transactions on Mobile Computing·2019· 25 citedOpen Access
Coarse2Fine: A Two-stage Training Method for Fine-grained Visual\n Classification
arXiv (Cornell University)·2019Open Access
A Meta-Learning Approach for Custom Model Training
Proceedings of the AAAI Conference on Artificial Intelligence·2019· 1 citedOpen Access
BottleNet: A Deep Learning Architecture for Intelligent Mobile Cloud Computing Services
2019· 9 citedOpen Access
Towards Collaborative Intelligence Friendly Architectures for Deep Learning
2019· 33 cited
BottleNet: A Deep Learning Architecture for Intelligent Mobile Cloud\n Computing Services
arXiv (Cornell University)·2019Open Access
Towards Collaborative Intelligence Friendly Architectures for Deep Learning
arXiv (Cornell University)·2019· 2 citedOpen Access
Towards Collaborative Intelligence Friendly Architectures for Deep\n Learning
arXiv (Cornell University)·2019Open Access
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Frequent Co-authors

Massoud Pedram(18), David Eigen(6), Amirhossein Esmaili(5), Mohammad Saeed Abrishami(4), Michael Gormish(4), João V. B. Soares(4), Kapil Thadani(4), Paloma de Juan(4), Priyank Pathak(2), Shaunak Mishra(2), Mikhail Kuznetsov(2), Yueh-Ning Ku(2), Mahdi Nazemi(2), Bhavin Jawade(2), Deen Dayal Mohan(2), Benjamin J. Culpepper(2), Srirangaraj Setlur(2), Venu Govindaraju(2), Yanzhi Wang(2), Shahin Nazarian(2)