72 Result(s)
within
**ngli Li
Artificial Intelligence
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Article
Distribution Linguistic Trust Propagation and Aggregation Based on Numerical Scale and Archimedean t−norm
Trust network analysis has been widely applied in various fields, such as group recommendation, group decision-making and other related areas. In this paper, we focus on obtaining the complete trust network in...
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Article
Open AccessTime Series Classification Based on Forward Echo State Convolution Network
The Echo state network (ESN) is an efficient recurrent neural network that has achieved good results in time series prediction tasks. Still, its application in time series classification tasks has yet to devel...
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Article
Multi-style image generation based on semantic image
Image generation has always been one of the important research directions in the field of computer vision. It has rich applications in virtual reality, image design, and video synthesis. Our experiments proved...
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Article
Open AccessDeep Embedding Clustering Based on Residual Autoencoder
Clustering algorithm is one of the most widely used and influential analysis techniques. With the advent of deep learning, deep embedding clustering algorithms have rapidly evolved and yield promising results....
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Chapter and Conference Paper
A Summary of Research on China Basic Education Evaluation with the Help of Intelligent Technology
Under the background of China Education Modernization 2035 and Education 4.0, promoting the integration and innovation of intelligent technology and basic education evaluation is the necessary path for educati...
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Chapter and Conference Paper
A Summary Research of the Current Status, Hot Spots and Trends in STEM Education
In the context of the publication of the “Thirteenth Five-Year Plan for Educational Informationization,” and China’s entry into the era of education informatization, the integration of information technology a...
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Chapter and Conference Paper
Exploration and Practice of Operating System Curriculum Reform Based on the Integration of Science and Education
Operating system (OS) is the core control of a computer, which serves as the command and management center of a computer, often referred to as the brain of a computer. Currently, operating systems are an impor...
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Chapter and Conference Paper
Research on the Teaching Model of Interdisciplinary Computational Thinking Cultivating from the Perspective of Problem-Solving
Computational thinking is a thinking process related to formal problems and their solutions, and the development of students’ computational thinking skills is one of the important objectives of basic IT teachi...
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Chapter and Conference Paper
DSAM-GN: Graph Network Based on Dynamic Similarity Adjacency Matrices for Vehicle Re-identification
In recent years, vehicle re-identification (Re-ID) has gained increasing importance in various applications such as assisted driving systems, traffic flow management, and vehicle tracking, due to the growth of...
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Article
Dense-scale dynamic network with filter-varying atrous convolution for semantic segmentation
Deep convolution neural networks (DCNNs) in deep learning have been widely used in semantic segmentation. However, the filters of most regular convolutions in DCNNs are spatially invariant to local transformat...
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Article
Modified fuzzy clustering algorithm based on non-negative matrix factorization locally constrained
The fuzzy C-means (FCM) algorithm is a classical clustering algorithm which is widely used. However, especially for high-dimensional data sets with complex structures, the large-scale calculation of FCM suffer...
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Article
Correction to: Embedded mutual learning: a novel online distillation method integrating diverse knowledge sources
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Article
Solving fuzzy scheduling using clustering method and bacterial foraging algorithm
Multi-objective fuzzy flexible job-shop scheduling problem (MFFJSSP) is a combination of multi-objective fuzzy scheduling and flexible job shop scheduling, which has higher complexity and is an NP-hard problem...
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Article
Embedded mutual learning: A novel online distillation method integrating diverse knowledge sources
Knowledge distillation (KD) is a feasible and effective way to obtain small networks with outstanding properties that can be deployed on hardware-constrained devices. Earlier KD methods were primarily implemen...
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Article
An algorithm of nonnegative matrix factorization under structure constraints for image clustering
Nonnegative matrix factorization (NMF) is a crucial method for image clustering. However, NMF may obtain low accurate clustering results because the factorization results contain no data structure information....
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Chapter and Conference Paper
A Quantitative Spectra Analysis Framework Combining Mixup and Band Attention for Predicting Soluble Solid Content of Blueberries
Hyperspectral imaging can rapid and non-destructive monitor physical characteristics and intrinsic chemical information of food. In recent years, many studies have applied hyperspectral imaging to evaluate the...
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Chapter and Conference Paper
Motion Imagery Classification Algorithm Based on Multiscale Convolution and Transfer Learning
Brain-computer interface is a new human-computer interaction technology that connects the human brain with external devices through computers and other electronic devices, and converts neural activity signals ...
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Article
Semi-supervised nonnegative matrix factorization with pairwise constraints for image clustering
Traditional clustering method is a kind of unsupervised learning, which is widely used in practical applications. However, the actual acquired data contains a part of prior information, that is the label of so...
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Chapter and Conference Paper
Cross-Stage Class-Specific Attention for Image Semantic Segmentation
Recent backbones built on transformers capture the context within a significantly larger area than CNN, and greatly improve the performance on semantic segmentation. However, the fact, that the decoder utilize...
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Chapter and Conference Paper
Blind Perceptual Quality Assessment for Single Image Motion Deblurring
Single image deblurring is a typical ill-posed problem. Although a lot of effective algorithms have been proposed, there is a lack of blind evaluation metrics for the perceptual quality of deblurred images. In...
