Building (Old Version) Caffe in Conda

A note of problems and solutions to compilation of an old version of caffe to verify 3Dpose_ssl project.

nn.Module: Network Construction

Background To define our network, we should succeed class nn.Module and implement the function forward. We put all the layers we want in the function __init__() and define how layers connect in function forward. Example class Hopenet(nn.Module): # Hopenet with 3 output layers for yaw, pitch and roll

Argparse

To use argparse module, we should only know a few functions. 1.Creating a parser parser = argparse.ArgumentParser(description='Head pose estimation using the Hopenet network.') 1.1.Function Details * description: Text to display before the argument help (default: none) By function: parser.print_help() we can get: usage:

History of Deepfake Media Detection

Abstract In 2017, Reddit user "deepfakes" posted several porn videos on the Internet which were not real, having been created with artificial intelligence. Deepfake is a portmanteau of "deep learning" and "fake", and a deep learning technique known as the generative adversarial network (GAN) is used to manipulate fake media

TensorFlow Implementation of DQN for Atari Games

Introduction Configuration win64+Python 3.7+Pycharm+OpenAI gym Prior knowledge In paper PlayingAtariwithDeepReinforcementLearning [https://www.cs.toronto.edu/~vmnih/docs/dqn.pdf], the author illuminates why he introduces deep learning into reinforcement learning (RL). The author wants to find a general solution to quite different games, and in order