Technical Name Energy EfficientHigh Performance Neural Network Accelerator / Real-time Full-HD Image Semantic SegmentationObject Detection Technology
Project Operator National Tsing Hua University
Project Host 林永隆
Summary
Low-power deep learning accelerator integrates neural network design / training, model compressionaccelerator design. It uses a small amount of computationmemory footprint to realize high performance on the edge device.
The image semantic segmentation technology can reach 80 frames per second (resolution:1024*2048) to meet real-time requirements for autonomous driving.
Scientific Breakthrough
1.	An AI engine that accelerates multi-layer fusion neural networks (each layer can be DNN, RNN, GRULSTM)
2.	Parameterized number of neurons for input/hidden/output layers 
3.	Smart model compression achieving 2 to 16 times compression ratio
4.	Configurable decimal point position for input, weight/biasoutput of each layer
5.	8 to 256 Configurable MACs
6.	Easy to use SDK
Industrial Applicability
Low-power deep learning accelerator can be widely used in IC design, communications, transportation, home appliances, consumer electronics, e-health etc. related industry. 
The image semantic segmentationobject detection technology can be used in autonomous driving, medical diagnosis, security surveillance, human-computer-interface, etc.
Keyword AI chip image semantic segmentation and object detection artificial neural networks network model compression Software Development Kit (SDK) autonomous driving speech command recognition hardware accelerator deep learning machine learning
Notes
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