Edge AI Accelerator

Low-Power Edge AI-Based Color Ball Detection on Microcontrollers for Gaming Machines

A low-power, TinierSSD-based color-ball detection model deployed on an ultra-low-power MAX78000 microcontroller for gaming machines. (M.S. thesis, 2025)

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HLS-Based YOLOv7-Tiny Accelerator for Infrared Ship-Target Detection

An HLS-based YOLOv7-Tiny hardware accelerator for real-time infrared ship-target detection on FPGA. (M.S. thesis, 2025)

An SoC based CNN Accelerator of Tiny-YOLOv2 for Blind Assistive System on FPGAs

With the development of Deep Learning, especially Convolutional Neural Networks (CNNs), there have been tremendous advances in neural networks for object detection. These models can accurately detect and categorize objects in a wide range of complex scenarios and have been practically applied in people's daily lives. However.....

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基於FPGA的可重構神經網路加速器應用於Tiny YOLO-V3

In recent year, the development of deep learning has been grown. According to the equipment updated and advanced, neural network could be handle has more and more things.....

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基於矩陣乘法架構進行記憶體存取優化的CNN加速器

卷積層是卷積神經網絡 (CNN) 推理階段中計算成本最高的部分。有許多架構被提出來有效地處理它。在這些設計中，具有高度流水線結構的脈動陣列能夠有效地加速通用矩陣-矩陣乘法 (GEMM)....

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An SoC-based CNN Accelerator for Face Recognition using HWCK data scheduling

In response to the promotion of the smart city and smart home, people pay more and more attention to the quality of life, wishing the technology could change our life....

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Design and Implementation of Low-Power, Energy-Efficient Neural Network Training Hardware Accelerators Based on Brain Floating-Point Computing and Sparsity Aware

we propose an efficient and flexible training processor called EESA. The proposed training processor features low power consumption, high throughput, and high energy efficiency....

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A Reconfigurable Hardware Architecture for Spatial Temporal Graph Convolution Network

Graph Convolutional Networks (GCNs) are well-suited for human action recognition using skeleton data, as they handle non-Euclidean structures like human joints and avoid issues with environmental noise affecting RGB images. However, GCNs often suffer from high latency and low power efficiency on CPU and GPU platforms due to computational complexity. To address this.....

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以深度神經網路實現手勢辨識及其硬體架構設計

The research in deep learning has become extensively deep recently, such as image pre-processing, image segmentation, object recognition, semantic analysis, etc. Deep learning has gradually replaced the traditional algorithm....

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