Original paper
A Real-Time Object Detection Accelerator with Compressed SSDLite on FPGA
Published: Dec 1, 2018
Abstract
Convolutional neural network (CNN)-based object detection has been widely employed in various applications such as autonomous driving and intelligent video surveillance. However, the computational complexity of conventional convolution hinders its application in embedded systems. Recently, a mobile-friendly CNN model SSDLite-MobileNetV2 (SSDLiteM2) has been proposed for object detection. This model consists of a novel layer called bottleneck...
Paper Details
Title
A Real-Time Object Detection Accelerator with Compressed SSDLite on FPGA
Published Date
Dec 1, 2018
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