Artificial Intelligence Review

This paper outlines a novel advanced framework that combines structurized knowledge and visual models—Computational Knowledge Vision. In advanced studies of image and visual perception, a visual model’s understanding and reasoning ability often ...

While the recent emergence of a large number of online course resources has made life more convenient for many people, it has also caused information overload. According to a user’s situation and behavior, course recommendation systems can ...

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 is rarely systematical review on these methods. In ...

In humans, Attention is a core property of all perceptual and cognitive operations. Given our limited ability to process competing sources, attention mechanisms select, modulate, and focus on the information most relevant to behavior. For decades, ...

With the advent of the Internet of Everything, the proliferation of data has put a huge burden on data centers and network bandwidth. To ease the pressure on data centers, edge computing, a new computing paradigm, is gradually gaining attention. ...

In his seminal paper of 2004, Ulrich Junker proposed the QuickXplain algorithm, which provides a divide-and-conquer computation strategy to find within a given set an irreducible subset with a particular (monotone) property. Beside its original ...

Current research on imbalanced data recognises that class imbalance is aggravated by other data intrinsic characteristics, among which class overlap stands out as one of the most harmful. The combination of these two problems creates a new and ...

Graph neural network is a deep learning approach widely applied on structural and non-structural scenarios due to its substantial performance and interpretability recently. In a non-structural scenario, textual and visual research topics like ...

Several deep learning algorithms have emerged for the automatic classification of environmental sounds. However, the non-availability of adequate labeled data for training limits the performance of these algorithms. Data augmentation is an ...

Online education has been facing difficulty in predicting the academic performance of students due to the lack of usage of learning process, summative data and a precise prediction of quantitative relations between variables and achievements. To ...

This paper provides a comprehensive review of automatic recognition of woven fabric structural parameters in recent years. Fabric structural parameters mainly include fabric density, weave pattern, color pattern, etc., which need to be pre-set ...

The separation of an object from other objects or the background by selecting the optimal threshold values remains a challenge in the field of image segmentation. Threshold segmentation is one of the most popular image segmentation techniques. The ...

In this manuscript, an intelligent hybrid approach is proposed to manage the power flow (PF) in the smart grid (SG) system. The proposed approach is the combined execution of Nomadic People Optimizer (NPO) algorithm and artificial transgender ...

Video super-resolution is currently one of the most active research topics in computer vision as it plays an important role in many visual applications. Generally, video super-resolution contains a significant component, i.e., motion compensation, ...

Automatic facial expression recognition is an active research area that has attracted much attention from both academics and practitioners of different fields. However, in reality, the problem of noise interference and cross-dataset expression ...

A fuzzy Petri net (FPN) is a powerful tool to model and analyze knowledge-based systems containing vague information. This paper systematically reviews recent developments of the FPN model from the following three perspectives: knowledge ...

Feature selection is an important task in the areas of pattern recognition and data mining. Various approaches to feature selection have been developed. In particular, this paper focuses on the algorithms for computing irreducible testors, which ...

Despite the extensive application of topic models in natural language processing tasks in recent years, the Chinese texts of short comments characterised by large scale, high noise and small information points have put forward higher requirements ...

Recently, deep CNN-based methods have achieved significant success in solving various 2D computer vision issues. However, directly processing 3D point clouds with CNNs remains a challenging problem due to their irregular characteristic, which ...$\mathbf{}\mathbf{}$

Assumption of fuzziness in the vehicle routing problems under extreme conditions is necessary for modelers, because there are usually insufficient objective input data. In extreme situations, the complexity of the description of vehicles’ movement ...