Neural networks have shown tremendous growth in recent years to solve numerous problems. Various types of neural been introduced deal with different However, the main goal any network is transform non-linearly separable input data into more linearly abstract features using a hierarchy layers. These layers are combinations linear and nonlinear functions. The most popular common non-linearity act...

In NLP research, unsupervised or semi-supervised learning techniques are increasingly getting more attention. These capable of from data that has not been manually annotated with the necessary answers by combining non-annotated and data. This essay presents a survey various natural language processing methods. The discipline processing, which integrates linguistics, artificial intelligence, com...

The application of deep architectures inspired by the fields artificial intelligence and computer vision has made a significant impact on task crack detection. As number studies being published in this field is growing fast, it important to categorize at deeper levels. In paper, comprehensive literature review learning-based detection contributions they have presented. are categorised according...

Video super-resolution (VSR) is reconstructing high-resolution videos from low resolution ones. Recently, the VSR methods based on deep neural networks have made great progress. However, there rarely systematical review these methods. In this survey, we comprehensively investigate 37 state-of-the-art learning. It well known that leverage of information contained in video frames important for su...