Jeong kisu kisuya

##Sequence to Sequence -- Video to Text

Download Model: S2VT_VGG_RGB_MODEL (333MB)

Deep Learning for Face Recognition (May 2016)

FaceNet (Google)
- They use a triplet loss with the goal of keeping the L2 intra-class distances low and inter-class distances high
DeepID (Hong Kong University)
- They use verification and identification signals to train the network. Afer each convolutional layer there is an identity layer connected to the supervisory signals in order to train each layer closely (on top of normal backprop)
DeepFace (Facebook)
- Convs followed by locally connected, followed by fully connected

CMake를 왜 쓰는거죠?
좋은 툴은 Visual Studio 뿐입니다. 그 이외에는 전부 사도(邪道)입니다 사도! - 작성자

이 문서는 CMake를 주관적으로 서술합니다
이 문서를 통해 CMake를 시작하기엔 적합하지 않습니다
https://cgold.readthedocs.io/en/latest/ 3.1 챕터까지 따라해본 이후 기본사항들을 속성으로 익히는 것을 돕기위한 보조자료로써 작성되었습니다

	qApp->setStyle(QStyleFactory::create("fusion"));

	QPalette palette;
	palette.setColor(QPalette::Window, QColor(53,53,53));
	palette.setColor(QPalette::WindowText, Qt::white);
	palette.setColor(QPalette::Base, QColor(15,15,15));
	palette.setColor(QPalette::AlternateBase, QColor(53,53,53));
	palette.setColor(QPalette::ToolTipBase, Qt::white);
	palette.setColor(QPalette::ToolTipText, Qt::white);
	palette.setColor(QPalette::Text, Qt::white);