Image restoration technology is a research hotspot in the field of deep learning computer vision. However, due to the complexity of facial textures, the existing face restoration algorithms lack visual coherence. We propose a face restoration algorithm (...

Emergency decision is the core module of intelligent monitoring system, which is related to the reliability and stability of system operation. But, the fault types are too numerous to be fully identified in advance. So, the emergency decision-making ...

With the continuous emergence of data, concept drift in data streams is becoming more and more common. In the past, concept drift detection was regarded as a task based on supervised learning, but it is of practical significance to study concept drift ...

In the process of pruning, in order to automatically obtain an optimal pruning threshold that can balance the maximum sparse rate and the minimum error. This paper proposes a convolutional neural network pruning algorithm based on the optimal threshold. ...

The number of wheat spikes per unit area is an important parameter for assessing wheat yield and wheat planting density. At present, the methods of intelligent counting of wheat include remote sensing technology and machine learning technology, but all ...

Zernike moments edge operator with 7x7 maskes is chosen as research object in this paper, principle deviation character of this operator caused by edge model is present, modified formula of edge translation 1 is deduced and given, it shows that the ...

This paper presents a hybrid deep learning network for the prediction of group-level emotion and cohesiveness. In this work, we first train deep models individually on face, pose, whole image, as well as fusion of them on Group Affect Dataset to predict ...

Text classification is a classic topic in natural language processing. In this study, we propose an attention model with multi-layer supervision for this task. In our model, the previous context vector is directly used as attention to select the ...

The purpose of this paper is to solve the problem that the local optimum is prone to arise in Semi-Supervised Sparse Representation based Classification (S3RC), so as to improve the classification effect. Although S3RC can solve the issue of face ...

The prediction of exchange rate is very important for both countries and enterprises. At present, the latest prediction technology is training BP neural network through the recent exchange rate data, and it takes effect in some degree. In view of the ...

Since the feature maps of deep neural networks were adopted to compute the representation of style and content information, neural style transfer (NST) methods have sprung up like mushrooms. But the existing methods ignore a fundamental fact that a ...

We present a new approach to recognize object and we test it in MNIST data set. The main purpose of this method is to solve some problems encountered by most current artificial intelligence. Firstly, most current artificial intelligence is ...

Melanoma is one of the most common human lethal cancers. Because the lesions have different shapes, sizes, colors, and low contrast, extracting powerful features for fine-grained skin lesion segmentation is still a challenging task today. In this paper, ...

Aspect Based Sentiment Analysis (ABSA) provides fine-grained sentiment information compared with traditional sentiment analysis. There are two approaches to the task, aspect term sentiment analysis (ATSA) and aspect category sentiment analysis (ACSA). ...

In finger vein recognition, traditional methods for extracting ROI based on edge detection, sliding window detection of joint lines, etc. need to set a fixed threshold, which contains many parameters that need to be adjusted. In the case of large ...

Relation classification is a basic and important task in the field of natural language processing(NLP). There are already many researches on English dataset, but the researches on Chinese dataset are very few. Due to the particularity of Chinese ...

Neural Question Generation is the use of deep neural networks to extract target answers from a given article or paragraph and generate questions based on the target answers. There is a problem in the previous NQG(Neural Question Generation) model, and ...

As a sub-task in natural language understanding, intent recognition research plays an important role in it. The accuracy of intent recognition is directly related to the performance of semantic slot filling, the choice of data set, and the research that ...

Face Reconstruction is an important research area in field of Computer Vision and Artificial Intelligence, and has a wide range of related applications in real life. Previous work primarily focuses on face feature extraction through images of real faces,...

Most of the existing evolutionary algorithms to deal with many-objective problems are based on the enhancing of selection strategy. Among them, the reference vector-guided evolutionary algorithm (RVEA) achieves excellent performance. In this paper, a ...