A Fully Spiking Hybrid Neural Network for Energy-Efficient Object Detection-Reference-Cited by-同舟云学术

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A Fully Spiking Hybrid Neural Network for Energy-Efficient Object Detection

Published:2021 Issue: Volume:30 Page:9014-9029
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Chakraborty Biswadeep^ORCID,She Xueyuan^ORCID,Mukhopadhyay Saibal

Funder

Defense Advanced Research Projects Agency

Army Research Office

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/9263394/09591302.pdf?arnumber=9591302

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Trainable Spiking-YOLO for low-latency and high-performance object detection;Neural Networks;2024-04

2. To Spike or Not to Spike: A Digital Hardware Perspective on Deep Learning Acceleration;IEEE Journal on Emerging and Selected Topics in Circuits and Systems;2023-12

3. Low Latency of Object Detection for Spiking Neural Network;2023 8th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC);2023-11-03

4. NeuSort: an automatic adaptive spike sorting approach with neuromorphic models;Journal of Neural Engineering;2023-09-13

5. Energy-Efficient Spiking Segmenter for Frame and Event-Based Images;Biomimetics;2023-08-10

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