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Mastering Github Pages: A Beginner’’s Guide

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應用模型壓縮技術並使用28奈米CMOS製程的23-FPS Tiny-YOLOv4物件辨識CNN晶片系統

為了解決GitHub Pages的問題，作者呂映承 這樣論述：

摘要...........................................................iAbstract......................................................iiAcknowledgements.............................................iiiContents......................................................ivList of Tables...............................

.................viList of Figures..............................................viiChapter 1 Introduction.......................................11.1 Object Detection...........................................11.2 Related Works..............................................21.2.1 Object De

tection CNN Models............................21.2.2 Optimization Techniques...............................101.2.3 Hardware Accelerators.................................161.3 Objectives................................................361.4 Thesis Organization..............................

.........37Chapter 2 Proposed System...................................382.1 Hardware Accelerator Implementation.......................382.2 Dataflow and FPS Estimation of the Hardware Accelerator...412.3 Proposed Object Detection CNN Model.......................432.4 Summary of the P

roposed System............................49Chapter 3 Experimental Results and Verification Results.....503.1 Implementation Environment................................503.2 System Implementation and Simulation......................513.3 Verification Environment..........................

........553.4 System Verification and Demonstration on FPGA.............553.5 Comparison to Related Works...............................57Chapter 4 Conclusion and Future Work..........................59Reference.....................................................60

Mastering Github Pages: A Beginner’’s Guide

為了解決GitHub Pages的問題，作者 這樣論述：