Elektro- och informationsteknik, Utbildning, Examensarbeten

Department of Electrical and Information Technology

Ricardo Nunez-Prieto, Pablo Correa Gomez & Liang Liu, 2019 Nov 21,  A Real-Time Gesture Recognition System with FPGA Accelerated ZynqNet Classification. Ricardo Nunez-Prieto, Pablo Correa Gomez & Liang Liu, 2019 nov 21,  ZynqNet CNN is a highly efficient CNN topology. Detailed analysis and optimization of prior topologies using the custom-designed Netscope CNN Analyzer have enabled a CNN with 84.5% top-5 accuracy at a computational complexity of only 530 million multiplyaccumulate operations. ZynqNet: An FPGA-Accelerated Embedded Convolutional Neural Network Edit social preview 14 May 2020 • David Gschwend ZynqNet CNN is a highly efficient CNN topology. Detailed analysis and optimization of prior topologies using the custom-designed Netscope CNN Analyzer have enabled a CNN with 84.5% top-5 accuracy at a computational complexity of only 530 million multiplyaccumulate operations.

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2021-04-08 · The ZynqNet FPGA Accelerator, a specialized FPGA architecture for the efficient acceleration of ZynqNet CNN and similar convolutional neural networks. ZynqNet CNN is trained offline on GPUs using the Caffe framework, while the ZynqNet FPGA Accelerator employs the CNN for image classification, or inference , on a Xilinx Zynq XC- 7Z045 System-on-Chip (SoC). The ZynqNet Embedded CNN is designed for image classification on ImageNet and consists of ZynqNet CNN, an optimized and customized CNN topology, and the ZynqNet FPGA Accelerator, an FPGA-based architecture for its evaluation. ZynqNet CNN is a highly efficient CNN topology. 2020-05-14 · The ZynqNet Embedded CNN is designed for image classification on ImageNet and consists of ZynqNet CNN, an optimized and customized CNN topology, and the ZynqNet FPGA Accelerator, an FPGA-based architecture for its evaluation. ZynqNet CNN is a highly efficient CNN topology.

Department of Electrical and Information Technology

Enjoy the videos and music you love, upload original content, and share it all with friends, family, and the world on YouTube. You need to save the files on a path without spaces (e.g. C:\zynqnet-master\ instead of "OK Zynqnet Master Complete/zynqnet-master"). The TB consists of: cpu_top.

Department of Electrical and Information Technology

ZynqNet CNN is a highly efficient CNN topology. ZynqNet: Modi cation ZynqNet was adapted for a gesture recognition system: • Optimizations to the FPGA Accelerator: • 8-bit xed-point scheme • No o -chip memory usage • Fine-tuning of the NN leads almost the same accuracy • Performance: 23.5 FPS 20 The SqueezeNet v1.1 and ZynqNet CNN algorithmic implementation is based on the adaptation and the extension of a Matlab project, 13 which, in its initial form, implements the floating-point (FLP) forward pass of the SqueezeNet v1.0 and compares it against the Caffe implementation for only a single predefined input image. FPGA-based ZynqNet CNN accelerator developed by Vivado_HLS Deep convolutional neural networks have dominated the pattern recognition scene by providing much more accurate solutions in computer vision problems such as object recognition and object detection. SqueezeNet is an 18-layer network that uses 1x1 and 3x3 convolutions, 3x3 max-pooling and global-averaging. One of its major components is the fire layer. Fire layers start out with a "squeeze" step (a few 1x1 convolutions) and lead to two "expand" steps, which include a 1x1 and a 3x3 convolution followed by concatenation of the two results. ZynqNet驱动： 当前的First Stage Boot Loader(FSBL)在zynqbox configuration中对programmable logic为FCLK_CLK0的时钟源100MHz，所以ZynqNet的FPGA accelerator只是运行了200MHz的一半。 在启动驱动之前，S_AXI HP0应被设置为32 bit bus width。 对于ZynqNet的FPGA加速器需要加载zynqnet_200MHz.bit.

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∙ 0 ∙ share . Image Understanding is becoming a vital feature in ever more applications ranging from medical diagnostics to autonomous vehicles. The ZynqNet Embedded CNN is designed for image classification on ImageNet and consists of ZynqNet CNN, an optimized and customized CNN topology, and the ZynqNet FPGA Accelerator, an FPGA-based architecture for its evaluation.

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Institutionen för elektro- och informationsteknik

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