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【CNN】YOLOv3模型详解 - Cornfield Chase

https://hugsy.top/2019/06/18/ML/cnn_yolov3/

2015年华盛顿大学的Joseph Redmon等人提出的YOLO算法中,将目标检测直接作为回归问题来解决,而使用一个一体化的CNN实现了端到端(End to End)检测,为目标检测问题提供了另外一种解决思路的同时,基于深度学习的目标检测算法也自此有了单步和多步之分。到2018年,YOLO已经更新到了v3版本,这里对该模型进行分析。

关于本站 - Cornfield Chase

https://hugsy.top/about/

更新历史 2017.09.12 以binweber.top为域名,‘binweber’为自己瞎编的名字,博客破壳日(●ˇ∀ˇ●) 2018.03.11 历时7个月,深度学习系列课程/笔记完结(●’◡’●) 2018.03.29 准备EE跨CS考研,博客暂停更新(づ ̄ 3 ̄)づ 2018.12.24 考研初试结束,准备以后二战/(ㄒoㄒ)/~~ 2019.04.01 做毕设

【Andrew Ng】深度学习(2):神经网络 - Cornfield Chase

https://hugsy.top/2017/09/25/ML/deep_learning_2/

神经网络(Neural Network)的构筑理念是受到生物神经网络功能的运作启发而产生的。人工神经网络通常是通过一个基于数学统计学类型的学习方法得以优化,所以人工神经网络也是数学统计学方法的一种实际应用。 和其他机器学习方法一样,神经网络已经被用于解决各种各样的问题,例如机器视觉和语音识别。这些问题都是很难被基于传统规则的编程解决的。

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