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應用於人體姿勢辨識與機器人之可重組深度神經網路引擎-子計畫四:應用可重組深度神經網路技術之姿勢與行為辨識系統(2/3)
Tsai, Tsung-Han
(PI)
電機工程學系
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研究成果
(2)
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Keyphrases
Classification Basis
100%
Lightweight Neural Network
100%
Data Augmentation
100%
Wafer Map Classification
100%
Electrocardiogram Compression
100%
Low-power Devices
100%
Compression Algorithms
100%
VLSI Implementation
100%
Reconfigurable
50%
Action Recognition
50%
Recognition System
50%
Human Pose Estimation
50%
Smart Home
50%
Depthwise Separable Convolution
50%
Test Accuracy
50%
Storage Space
50%
Transmission Time
50%
Light Level
25%
Representative Bodies
25%
Care Homes
25%
Voice Behavior
25%
Wearable Devices
25%
Pre-setting
25%
Classification Applications
25%
Air Conditioning
25%
Cuda
25%
Infrared Camera
25%
Main Trends
25%
RealSense
25%
Operating Environment
25%
Conditioning Temperature
25%
Human Behavior
25%
Speech Recognition
25%
Dual Camera
25%
Traditional Algorithm
25%
Health Smart Home
25%
Vision Technology
25%
Automatically Adjust
25%
Artificial Intelligence Applications
25%
Object Classification
25%
Stereo Vision
25%
Real Environment
25%
Part Feature
25%
Ordinary Users
25%
Recognition Classification
25%
Smart Home System
25%
Face Recognition
25%
Real-time Processing
25%
Body Parts
25%
Color Image
25%
AI Technology
25%
Depth Image
25%
Kinect
25%
Deep Neural Network
25%
KHz Frequency
25%
Accurate Classification
25%
Production Volume
25%
Semiconductor Industry
25%
Neural Network
25%
Taiwan
25%
Map Data
25%
Encoder-decoder
25%
Defect Classification
25%
MobileNetV1
25%
Data Defects
25%
Number of Parameters
25%
CNN Encoder
25%
Wafer Map
25%
Open Dataset
25%
WM-811K
25%
Different Datasets
25%
Efficient Power
25%
Content Adaptive
25%
Bit Compression
25%
Arithmetic Operations
25%
Prediction Method
25%
Lossless Compression
25%
MIT-BIH Arrhythmia Database
25%
Memoryless
25%
Bit Shift
25%
VLSI Architecture
25%
Electrocardiogram Data
25%
Adaptive Linear Prediction
25%
Golomb-Rice Code
25%
Data Encoding
25%
Compression System
25%
Shift Operation
25%
90-nm CMOS Technology
25%
Clock Frequency
25%
VLSI Design
25%
Low Power VLSI
25%
CMOS Process
25%
Compression Rate
25%
Gate Count
25%
Engineering
Power Device
100%
Test Dataset
100%
Neural Network Weight
100%
Compression Algorithm
100%
Defect Classification
100%
Model Parameter
100%
Large Production Volume
100%
Convolutional Neural Network
100%
Pose Estimation
50%
Artificial Intelligence
50%
Real Life
33%
Smart Home
33%
Lossless Compression
25%
Rice Code
25%
Clock Speed
25%
Compression Scheme
25%
Infrared Camera
16%
Light Level
16%
Stereovision
16%
Body Part
16%
Air Conditioning
16%
Wearable Sensor
16%
Camera Stream
16%
Operating Environment
16%
Smart Home Application
16%
Color Image
16%
Deep Neural Network
16%
Health Care
16%