Spikebased Neuromorphic Computing For Nextgeneration Computer Vision
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**arXiv ID:** 2310.09692 **Authors:** Md Sakib Hasan, Catherine D. Schuman, Zhongyang Zhang, Tauhidur Rahman, Garrett S. Rose **Published:** 2023-10-15T01:05:35Z **Abstract:** Neuromorphic Computing promises orders of magnitude improvement in energy efficiency compared to traditional von Neumann computing paradigm. The goal is to develop an adaptive, fault-tolerant, low-footprint, fast, low-energy intelligent system by learning and emulating brain functionality which can be realized through i...
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# Spike-based Neuromorphic Computing for Next-Generation Computer Vision
**arXiv ID:** 2310.09692
**Authors:** Md Sakib Hasan, Catherine D. Schuman, Zhongyang Zhang, Tauhidur Rahman, Garrett S. Rose
**Published:** 2023-10-15T01:05:35Z
**Abstract:**
Neuromorphic Computing promises orders of magnitude improvement in energy efficiency compared to traditional von Neumann computing paradigm. The goal is to develop an adaptive, fault-tolerant, low-footprint, fast, low-energy intelligent system by learning and emulating brain functionality which can be realized through innovation in different abstraction layers including material, device, circuit, architecture and algorithm. As the energy consumption in complex vision tasks keep increasing exponentially due to larger data set and resource-constrained edge devices become increasingly ubiquitous, spike-based neuromorphic computing approaches can be viable alternative to deep convolutional neural network that is dominating the vision field today. In this book chapter, we introduce neuromorphic computing, outline a few representative examples from different layers of the design stack (devices, circuits and algorithms) and conclude with a few exciting applications and future research directions that seem promising for computer vision in the near future.
## Skill Description
This skill is generated from the arXiv paper: Spike-based Neuromorphic Computing for Next-Generation Computer Vision (2310.09692).
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## References
- [arXiv:2310.09692](http://arxiv.org/abs/2310.09692v2)
