… -resolution reconstruction method based on deep learning are analyzed and compared.
Finally, the future development trend of image superresolution reconstruction is prospected. …

… It first summarizes recent progress in traditional handcrafted feature based methods, and
then introduces the deep learning based steganalysis, which is a new trend in steganalysis. …

… What we need now is not blind adoration and beatification of the past but deeper awareness
of its immense complexity, of both its positive and its negative features. Only then will we be …

… The proposed approach is analyzed for blind channel scenarios … Recently, evolution of
deep learning for pattern recognition has … Blind recognition of linear space-time block codes: a …

… -orthogonal multiple access in the code domain. Data can be … in unlicensed sparse coding
multiple access scenarios. … , we propose to use a deep neural network (DNN) to directly …

… 神經網路(Complex-valued Deep neural network),來學習混合訊號之… 摘要(英) Deep neural
networks (DNNs) have become a … -valued deep neural network is developed herein to learn the …

… reception technology based on deep learning at home and … Signal processing based deep
learning for blind symbol … Reduced-complexity deep neural network-aided channel code …

… This dissertation also develops two novel methods for back-end recognition. The first is a
joint kernel dictionary learning (JKDL) method for sound event classification. Our JKDL learns …

… Deep neural networks gained the … recognition, image classification, sound recognition,
image generation and especially monaural source separation. However, deep neural networks (…