FPGA design and hardware implementation of a convolutional neural network for classification of saccadic eye movements

Carlos Cano Domingo; Ruxandra Stoean; Gonzalo Joya Caparros

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FPGA design and hardware implementation of a convolutional neural network for classification of saccadic eye movements

机译：FPGA设计和硬件实现卷积神经网络，用于扫视眼球运动的分类

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The paper presents an efficient design and implementation of a convolutional neural network on an FPGA device. The aim is not only theoretical but also practical, since the solution will be used in a medical clinic dealing with SpinoCerebellar Ataxia type 2 as part of a larger project. Hence, the current work targets both high learning capabilities as well as portability. The former has been tackled through the apppointment a convolutional neural network while the latter is concerned with the hardware implementation of the complex network on a FPGA. The preliminary results encourage the further exploitation of the proposed solution.

机译：本文介绍了FPGA设备上卷积神经网络的有效设计和实现。目的不仅是理论且也是实用的，因为该解决方案将用于处理Spinocerebellar Ataxia类型2的医学诊所，作为较大项目的一部分。因此，目前的工作是高学习能力以及可移植性。前者已经通过Appportport，卷积神经网络进行了解决，而后者涉及FPGA上复杂网络的硬件实现。初步结果鼓励进一步利用所提出的解决方案。

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《University of Bucharest. Annals. Mathematical Series》 |2018年第2期|共12页
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Carlos Cano Domingo; Ruxandra Stoean; Gonzalo Joya Caparros;
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1. FPGA design and hardware implementation of a convolutional neural network for classification of saccadic eye movements [J] . Carlos Cano Domingo, Ruxandra Stoean, Gonzalo Joya Caparros Universitatea din Craiova. Analele. Seria: Matematica, Informatica . 2018,第2期

机译：卷积神经网络的FPGA设计和硬件实现，用于对眼球运动进行分类
2. RSNN: A Software/Hardware Co-Optimized Framework for Sparse Convolutional Neural Networks on FPGAs [J] . Weijie You, Chang Wu Quality Control, Transactions . 2021,第1期

机译：RSNN：FPGA上的稀疏卷积神经网络的软件/硬件共同优化框架
3. A Survey of Algorithmic and Hardware Optimization Techniques for Vision Convolutional Neural Networks on FPGAs [J] . Sateesan Arish, Sinha Sharad, Smitha K. G., Neural processing letters . 2021,第3期

机译：对FPGA的视觉卷积神经网络算法和硬件优化技术调查
4. Unsupervised Learning as a Complement to Convolutional Neural Network Classification in the Analysis of Saccadic Eye Movement in Spino-Cerebellar Ataxia Type 2 [C] . Catalin Stoean, Ruxandra Stoean, Roberto Antonio Becerra-Garcia, International Work-Conference on Artificial Neural Networks . 2019

机译：无监督学习作为对卷积神经网络分类的补充，以分析脊髓小脑性共济失调2型眼跳运动
5. Classification of Road Side Material Using Convolutional Neural Network and a Proposed Implementation of the Network Through Zedboard Zynq 7000 FPGA [D] . Rahman, Tanvir. 2017

机译：使用卷积神经网络对路边物料进行分类以及通过Zedboard Zynq 7000 FPGA进行网络的拟议实现
6. FPGA Implementation for Odor Identification with Depthwise Separable Convolutional Neural Network [O] . Zhuofeng Mo, Dehan Luo, Tengteng Wen, 2021

机译：FPGA实现气味识别与深度可分离的卷积神经网络
7. CNN2Gate: An Implementation of Convolutional Neural Networks Inference on FPGAs with Automated Design Space Exploration [O] . Alireza Ghaffari, Yvon Savaria 2020

机译：CNN2GATE：自动化设计空间探索对FPGA的卷积神经网络推断的实现

FPGA design and hardware implementation of a convolutional neural network for classification of saccadic eye movements

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