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ORCIDMd Fahim Faysal Khan
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2020 – today
- 2024
[c7]Anusha Devulapally, Md Fahim Faysal Khan, Siddharth Advani, Vijaykrishnan Narayanan:
Multi-Modal Fusion of Event and RGB for Monocular Depth Estimation Using a Unified Transformer-based Architecture. CVPR Workshops 2024: 2081-2089- 2023
- [c6]Sadia Anjum Tumpa, Sonali Singh, Md Fahim Faysal Khan
, Mahmut Taylan Kandemir, Vijaykrishnan Narayanan, Chita R. Das:
Federated Learning with Spiking Neural Networks in Heterogeneous Systems. ISVLSI 2023: 1-6 - 2022
- [c5]Chonghan Lee, Md Fahim Faysal Khan, Rita Brugarolas Brufau, Ke Ding, Vijaykrishnan Narayanan:
Token and Head Adaptive Transformers for Efficient Natural Language Processing. COLING 2022: 4575-4584 - [c4]Md Fahim Faysal Khan, Anusha Devulapally, Siddharth Advani, Vijaykrishnan Narayanan:
Robust Multimodal Depth Estimation using Transformer based Generative Adversarial Networks. ACM Multimedia 2022: 3559-3568 - 2021
- [c3]Md Fahim Faysal Khan, Nelson Daniel Troncoso Aldas, Abhishek Kumar, Siddharth Advani, Vijaykrishnan Narayanan:
Sparse to Dense Depth Completion using a Generative Adversarial Network with Intelligent Sampling Strategies. ACM Multimedia 2021: 5528-5536 - 2020
- [c2]Md Fahim Faysal Khan, Mohammad Mahdi Kamani, Mehrdad Mahdavi, Vijaykrishnan Narayanan:
Learning to Quantize Deep Neural Networks: A Competitive-Collaborative Approach. DAC 2020: 1-6
2010 – 2019
- 2019
- [c1]Md Fahim Faysal Khan, Nicholas Anton Jao, Changchi Shuai, Keni Qiu, Mehrdad Mahdavi, Vijaykrishnan Narayanan:
Mixed Precision Quantization Scheme for Re-configurable ReRAM Crossbars Targeting Different Energy Harvesting Scenarios. IFIPIoT 2019: 197-216
Coauthor Index
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