Learning Deep Features for Discriminative Localization
“Learning Deep Features for Discriminative Localization” proposed a method to enable the convolutional neural network to have localization ability despite be...
Recent Posts
Hide-and-Seek
“Hide-and-Seek: Forcing a Network to be Meticulous for Weakly-supervised Object and Action Localization” proposed a weakly-supervised framework to improve ob...
Loss Functions
When we train a deep learning model, we need to set a loss function for minimizing the error. The loss function indicates how much each variable contributes ...
Attention Is All You Need
The paper “Attention is all you need” from google propose a novel neural network architecture based on a self-attention mechanism that believe to be particul...
Optimization
It is always important what kind of optimization algorithm to use for training a deep learning model. According to the optimization algorithm we use, the mod...
Vision Technique
Research on several vision techniques such as pixel difference and optical flow.
Approximate Inference
Approximate inference methods make it possible to learn realistic models from big data by trading off computation time for accuracy, when exact learning and ...
Autoencoder
Autoencoder is an artificial neural network used for unsupervised learning of efficient codings. The aim of an autoencoder is to learn a representation (enco...