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ivjia's Projects

deep-learning-v2-pytorch icon deep-learning-v2-pytorch

Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

deepface icon deepface

Face analysis mainly based on Caffe. At this time, face analysis tasks like detection, alignment and recognition have been done.

deeplearning-500-questions icon deeplearning-500-questions

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15个章节,近20万字。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

deepo icon deepo

A series of Docker images (and their generator) that allows you to quickly set up your deep learning research environment.

deepviz icon deepviz

Visualization tools for deep convolutional networks

detectron icon detectron

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

detr icon detr

End-to-End Object Detection with Transformers

discover icon discover

Custom bash scripts used to automate various penetration testing tasks including recon, scanning, enumeration, and malicious payload creation using Metasploit. For use with Kali Linux.

documentation icon documentation

https://docs.chain.link The Chainlink developer documentation website for Smart Contract Devs and Node Operators

end2end-all-conv icon end2end-all-conv

End-to-end training for breast cancer diagnosis using deep all convolutional networks

face-frontalization icon face-frontalization

This is a port of the Face Frontalization code provided by Hassner et al. at http://www.openu.ac.il/home/hassner/projects/frontalize

face-sketch-wild icon face-sketch-wild

Semi-Supervised Learning for Face Sketch Synthesis in the Wild, ACCV2018

facenet icon facenet

Tensorflow implementation of the FaceNet face recognizer

facerecognizer icon facerecognizer

:boy: A face recognition algorithm which notifies you on facebook in case of an Intruder attack

fast-marl icon fast-marl

FAST iteration of MARL research ideas: A starting point for Multi-Agent Reinforcement Learning

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