An overview of Human Action Recognition in sports based on Computer Vision
K Host, M Ivašić-Kos - Heliyon, 2022 - cell.com
Abstract Human Action Recognition (HAR) is a challenging task used in sports such as
volleyball, basketball, soccer, and tennis to detect players and recognize their actions and …
volleyball, basketball, soccer, and tennis to detect players and recognize their actions and …
A survey of accelerator architectures for 3D convolution neural networks
S Mittal - Journal of Systems Architecture, 2021 - Elsevier
Abstract 3D convolution neural networks (CNNs) have shown excellent predictive
performance on tasks such as action recognition from videos. Since 3D CNNs have unique …
performance on tasks such as action recognition from videos. Since 3D CNNs have unique …
A real-time object detection accelerator with compressed SSDLite on FPGA
Convolutional neural network (CNN)-based object detection has been widely employed in
various applications such as autonomous driving and intelligent video surveillance …
various applications such as autonomous driving and intelligent video surveillance …
F-E3D: FPGA-based acceleration of an efficient 3D convolutional neural network for human action recognition
Three-dimensional convolutional neural networks (3D CNNs) have demonstrated their
outstanding classification accuracy for human action recognition (HAR). However, the large …
outstanding classification accuracy for human action recognition (HAR). However, the large …
FPGA-based acceleration for Bayesian convolutional neural networks
Neural networks (NNs) have demonstrated their potential in a variety of domains ranging
from computer vision (CV) to natural language processing. Among various NNs, two …
from computer vision (CV) to natural language processing. Among various NNs, two …
Mapping large LSTMs to FPGAs with weight reuse
Abstract Long-Short Term Memory (LSTM) can retain memory and learn from data
sequences. It gives state-of-the-art accuracy in many applications such as speech …
sequences. It gives state-of-the-art accuracy in many applications such as speech …
An FPGA-based upper-limb rehabilitation device for gesture recognition and motion evaluation using multi-task recurrent neural networks
Upper-Extremity motor impairment affects millions of Americans due to cerebrovascular
incidents, spinal cord injuries, or brain trauma. Current therapy practices used to assist these …
incidents, spinal cord injuries, or brain trauma. Current therapy practices used to assist these …
Number systems for deep neural network architectures: a survey
Deep neural networks (DNNs) have become an enabling component for a myriad of artificial
intelligence applications. DNNs have shown sometimes superior performance, even …
intelligence applications. DNNs have shown sometimes superior performance, even …
High-performance acceleration of 2-D and 3-D CNNs on FPGAs using static block floating point
Over the past few years, 2-D convolutional neural networks (CNNs) have demonstrated their
great success in a wide range of 2-D computer vision applications, such as image …
great success in a wide range of 2-D computer vision applications, such as image …
Harflow3d: A latency-oriented 3d-cnn accelerator toolflow for har on fpga devices
P Toupas, A Montgomerie-Corcoran… - 2023 IEEE 31st …, 2023 - ieeexplore.ieee.org
For Human Action Recognition tasks (HAR), 3D Convolutional Neural Networks have
proven to be highly effective, achieving state-of-the-art results. This study introduces a novel …
proven to be highly effective, achieving state-of-the-art results. This study introduces a novel …