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LanguageMPC: Large Language Models as Decision Makers for Autonomous Driving
Existing learning-based autonomous driving (AD) systems face challenges in comprehending high-level information, generalizing to rare events, and providing interpretability.
GnetDet: Object Detection Optimized on a 224mW CNN Accelerator Chip at the Speed of 106FPS
Object detection is widely used on embedded devices.
GnetSeg: Semantic Segmentation Model Optimized on a 224mW CNN Accelerator Chip at the Speed of 318FPS
In this paper, we optimize the semantic segmentation model in order to fully utilize the limited memory and the supported operators on the CNN accelerator chips, and at the same time reduce the CPU load of the CNN model to zero.
SuperOCR: A Conversion from Optical Character Recognition to Image Captioning
The existing methods normally detect where the characters are, and then recognize the character for each detected location.
Multi-modal Sentiment Analysis using Super Characters Method on Low-power CNN Accelerator Device
Recent years NLP research has witnessed the record-breaking accuracy improvement by DNN models.
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