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图文教程搭建一个vpn翻墙
深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,近30万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系[email protected] 版权所有,违权必究 Tan 2018.06
my graduate design
tensorflow implementation of Grad-CAM (CNN visualization)
Two multitasking CNNs for simultaneous face detection, landmarks estimation and visibility, pose estimation and gender recognition. hyperface.py concatenates feature maps from initial, mid and final layers of the network and then branches out to different heads. multiout.py branches from the final layer of the network to different heads. DataGen2.py is the Data Generator used for reading multiple labels from json files. It is a modified version of Keras's default Data Generator. The idea is based on the following paper - [1] R. Ranjan, V. M. Patel, and R. Chellappa. Hyperface: A deep multitask learning framework for face detection, landmark localization, pose estimation, and gender recognition. CoRR, abs/1603.01249, 2016. The implementation is slightly different. The original HyperFace architecture is built on top of AlexNet while the implementation here uses another architecture called SqueezeNet.
Evaluation of Labeled Faces in the Wild (LFW Face Database).
Models and examples built with TensorFlow
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