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改變未來20年最重要的20個視覺機器學習理論深讀
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改變未來20年最重要的20個視覺機器學習理論深讀 
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作者:謝劍斌,興軍亮,張立甯,方宇強,李沛秦,劉通,閆瑋,王勇,沈傑,張政,譚筠,胡俊
出版社:佳魁資訊
出版日期:2016年06月27日
語言:繁體中文
版別:初版
装订:平裝
页数:296
印刷:單色印刷
分級:普級
ISBN:9789863793434

內容簡介



本書是12 位博士多年研究視覺機器學習的基礎理論、核心演算法、關鍵技術和應用實作的科學結晶,是作者們多年相關科學研究實作的心得體會和系統歸納。包含K-Means、KNN 學習、回歸學習、決策樹學習、Random Forest、貝氏學習、EM 方法、AdaBoost、SVM 方法、增強學習、流形學習、RBF 學習、稀疏表示、字典學習、BP 學習、CNN 學習、RBM 學習、深度學習、遺傳方法、粒子群方法、蟻群方法共20 個常用視覺機器學習方法。進行深入淺出的說明,以簡單明瞭、豐富圖表、解釋程式、應用為宗旨。



本書特別重視如何將視覺機器學習演算法的理論和實踐結合,解決視覺機器學習領域中的諸多基礎問題,可應用於醫學影像分析、工業自動化、機器人、無人車、人臉檢測與識別、車輛資訊識別、行為檢測與識別、智慧視訊監控等領域。



書中範例原始程式碼,可至佳魁資訊官網下載



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