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2020 – today
- 2024
[j3]Hasib-Al Rashid
, Utteja Kallakuri, Tinoosh Mohsenin:
TinyM2Net-V2: A Compact Low-power Software Hardware Architecture for Multimodal Deep Neural Networks. ACM Trans. Embed. Comput. Syst. 23(3): 47:1-47:23 (2024)- [c4]Uttej Kallakuri, Edward Humes, Tinoosh Mohsenin:
Resource-Aware Saliency-Guided Differentiable Pruning for Deep Neural Networks. ACM Great Lakes Symposium on VLSI 2024: 694-699 - 2022
- [j2]Aidin Shiri, Uttej Kallakuri, Hasib-Al Rashid, Bharat Prakash, Nicholas R. Waytowich, Tim Oates, Tinoosh Mohsenin:
E2HRL: An Energy-efficient Hardware Accelerator for Hierarchical Deep Reinforcement Learning. ACM Trans. Design Autom. Electr. Syst. 27(5): 45:1-45:19 (2022) - 2021
- [j1]Arnab Neelim Mazumder, Jian Meng, Hasib-Al Rashid, Utteja Kallakuri, Xin Zhang, Jae-Sun Seo, Tinoosh Mohsenin:
A Survey on the Optimization of Neural Network Accelerators for Micro-AI On-Device Inference. IEEE J. Emerg. Sel. Topics Circuits Syst. 11(4): 532-547 (2021) - [c3]Hasib-Al Rashid, Arnab Neelim Mazumder, Utteja Panchakshara Kallakuri Niyogi, Tinoosh Mohsenin:
CoughNet: A Flexible Low Power CNN-LSTM Processor for Cough Sound Detection. AICAS 2021: 1-4
2010 – 2019
- 2019
- [c2]Morteza Hosseini, Mark Horton, Hiren Paneliya, Uttej Kallakuri, Houman Homayoun, Tinoosh Mohsenin:
On the Complexity Reduction of Dense Layers from O(N2) to O(NlogN) with Cyclic Sparsely Connected Layers. DAC 2019: 203 - [c1]Morteza Hosseini, Hirenkumar Paneliya, Utteja Kallakuri, Mohit Khatwani, Tinoosh Mohsenin:
Minimizing Classification Energy of Binarized Neural Network Inference for Wearable Devices. ISQED 2019: 259-264
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