We, the Deep Learning research group of WEBLAB, are developing the future of artificial intelligence technologies. Our activities cover not only researches but also education and development.
FacialVAE – Conditional VAE-GAN with Attribute Inference for Faces
A generative model for faces based on Conditional VAE-GAN. Demo – M. Suzuki
Deep X-ray image processing for diagnosis support
Realtime Instance Recognition for Desktop Objects
TBA – K. Nakayama, et al.
Trend Prediction with Recurrent Neural Networks
TBA. – N. Nonaka, et al.
Deep Activity Recognition for Wheelchairs
Sensors, CNN, Model Compression for limited resource environment. – Y. Iwasawa
Evolutional deep learning algorithms towards flexible networks. – H. Kurotaki
GeSdA – GPU empowered Stacked denoising Autoencoder
High-performance Stacked denoising Autoencoder enhanced by CrossPre (Cross-Layer Pretraining). – K.Nakayama