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Graph-based scale-aware network for human parsing 1

2nd Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2019

作者： Yang, Beibei Yu, Changqian Liu, Jiahui Gao, Changxin Sang, Nong Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9783030317232

ISBN: (纸本)9783030317225

Recent work has made considerable progress in exploring contextual information for human parsing with the Fully Convolutional Network framework. However, there still exist two challenges: (1) inherent relative relationships between parts;(2) scale variation of human parts. To tackle both problems, we propose a Graph-Based Scale-Aware Network for human parsing. First, we embed a Graph-Based Part Reasoning Layer into the backbone network to reason the relative relationship between human parts. Then we construct a Scale-Aware Context Embedding Layer, which consists of two branches to capture scale-specific contextual information, with different receptive fields and scale-specific supervisions. In addition, we adopt an edge supervision to further improve the performance. Extensive experimental evaluations demonstrate that the proposed model performs favorably against the state-of-the-art human parsing methods. More specifically, our algorithm achieves 53.32% (mIoU) on the LIP dataset. © Springer Nature Switzerland AG 2019.

关键词： Embeddings

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The design and implementation of a Chinese financial invoice recognition system

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Journal of Quantitative Linguistics 2002年第1期9卷 19-33页

作者： Ming, Delie Liu, Jian Tian, Jinwen State Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan Hubei Province 430074 China

This paper designs and implements a financial invoice recognition system based on the features of the Chinese financial invoice. By using the linear whole block moving method in each vertical segment, a new fast algorithm is put forth to detect and rectify the slant image. To distinguish the different form types (the foundation necessary for locating the form fields, filtering the form lines, etc.), several representative form features are discussed and an invoice-type features library is built by using a semi-automatic machine study method. On the basis of the recognized invoice type, real invoice form is re-oriented against the corresponding blank form according to the invoice type feature, solving the problem of adhesion of characters and form lines, as well as the problem of character segmentation and recognition. Based on the Chinese financial invoice image feature, a mutual rectification mechanism founded on the recognition results of Chinese financial characters and Arabic numerals is put forward to raise the recognition rate. Finally, the experimental results and conclusions are presented. © Swets & Zeitlinger.

关键词： LINGUISTICS WORD recognition -- Software

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Exploring the impact of processing temperatures on cod protein modifications by α, β-unsaturated aldehydes using a clickable probe

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Food Chemistry 2025年 486卷 144683页

作者： Jiang, Kaiyu Gong, Wei Liang, Yu-Xuan Tu, Juncai Li, Jinjin Gao, Weiman Dong, Xiuping Zhu, Beiwei Shenzhen Key Laboratory of Food Nutrition and Health College of Chemistry and Environmental Engineering and Institute for Innovative Development of Food Industry Shenzhen University Shenzhen518060 China Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging National- Regional Key Technology Engineering Laboratory for Medical Ultrasound School of Biomedical Engineering Shenzhen University Medical School Shenzhen518060 China Department of Food Science and Engineering College of Biological Sciences and Biotechnology Beijing Key Laboratory of Forest Food Processing and Safety Beijing Forestry University Beijing100083 China State Key Laboratory of Marine Food Processing and Safety Control Dalian Polytechnic University Dalian116034 China National Engineering Research Center of Seafood Collaborative Innovation Center of Seafood Deep Processing School of Food Science and Technology Dalian Polytechnic University Dalian116034 China

To investigate the effects of processing temperatures on α, β-unsaturated aldehyde-mediated modifications of cod protein, a clickable probe, 4-(2-Propyn-1-yloxy)-2-butenal (yne-ACR), was developed to simulate α, β-unsaturated aldehyde modifications on cod protein in simulated processing systems (25 °C, 90 °C, and 180 °C). processing at 180 °C resulted in a 3-fold increase in the hydrophobicity, while modifications under thermal processing had limited effects on the content of free nucleophilic amino acids. However, modification at 180 °C significantly increased the content of carbonylated proteins to 14.7 nmol/mg protein. Cod protein modified during thermal processing (90 °C and 180 °C) exhibited superior emulsifying and foaming properties than those subjected to heating alone. Cod protein processed at 90 °C exhibited 757 identified modified components, representing the highest number among the three processing temperatures, and thermally induced structural changes in cod protein facilitated multiple modifications on a single peptide. These findings provide new tools and insights for the study of food protein modification. © 2025 Elsevier Ltd

关键词： Carbonylation

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Classification of transgenic corn varieties using terahertz spectroscopy and convolutional neural network

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Journal of Food Composition and Analysis 2025年 145卷

作者： Yuying Jiang Xixi Wen Hongyi Ge Guangming Li Hao Chen Mengdie Jiang Qingcheng Sun Shilei Wei Peng Li Key Laboratory of Grain Information Processing and Control Henan University of Technology Ministry of Education Zhengzhou 450001 China Henan Provincial Key Laboratory of Grain Photoelectric Detection and Control Henan University of Technology Zhengzhou 450001 China School of Artificial Intelligence and Big Data Henan University of Technology Zhengzhou 450001 China School of Information Science and Engineering Henan University of Technology Zhengzhou 450001 China Institute for Complexity Science Henan University of Technology Zhengzhou 450001 China

Corn is the largest grain crop in China. With the increasing use of transgenic corn in agricultural production, accurately identifying transgenic corn varieties has become crucial for ensuring food safety and quality. This study combines terahertz time-domain spectroscopy (THz-TDS) technology with a convolutional neural network (CNN) to classify five transgenic corn varieties. First, the time-domain spectra of transgenic corn were collected, and the frequency-domain spectra and absorption coefficient spectra were calculated. Next, abnormal data were removed using the isolation forest algorithm. The data were then preprocessed using the first derivative (FD) and principal component analysis (PCA) to extract effective spectral features. Based on these features, classification models were constructed using support vector machine (PCA-SVM), grid search optimized SVM (PCA-GS-SVM), particle swarm optimization SVM (PCA-PSO-SVM), and hippopotamus optimization SVM (PCA-HO-SVM). Additionally, a one-dimensional CNN (1D-CNN) model was built using the full-band spectral data. The results indicate that the performance of the 1D-CNN model with FD preprocessing was significantly improved, with an accuracy of 96.68 % and a misclassification rate of only 3.32 %. The study effectively classifies transgenic corn with high accuracy, showing potential for widespread application in quality detection.

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Route planning based on gradient-field quantum genetic algorithm model

Journal of Software

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Journal of Software 2013年第10期8卷 2511-2516页

作者： Sun, Yangguang Ding, Mingyue College of Computer Science South-Central University for Nationalities State Key Laboratory of Software Engineering Wuhan University Wuhan 430074 China School of Life Science and Technology 'Image Processing and Intelligence Control' Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China

A route planning method based on gradient-field quantum genetic algorithm model was presented in this paper. It introduces the gradient field of a grid map to quantum genetic algorithm model and uses quantum genetic algorithm (QGA) to optimize the cost function of route planning. By combining the quantum characteristics with the capabilities of the large diversity of the population, as well as fast convergence rate and high global searching, the optimization of route was guided and realized in our method by using the genetic operators with the essential characteristics of quantum and the gradient information of a grid map. Experimental results demonstrated that our method further effectively improves the quick convergence and capability of searching the optimal route. © 2013 ACADEMY PUBLISHER.

关键词： Cost functions

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controllability of neighborhood Corona product networks

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Science China(Information Sciences) 2024年第12期67卷 327-328页

作者： Bo LIU Xuan LI Qiang ZHANG Junjie HUANG Housheng SU Ministry of Education Key Laboratory for Intelligent Analysis and Security Governance of Ethnic Languages School of Information Engineering Minzu University of China School of Mathematical Sciences Inner Mongolia University Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology

controlling networks aims to study the models, structures,and related dynamics of complex networks. The primary problem of controlling networks is to determine whether they are controllable. Nowadays, controllability has been widely studied and applied to system engineering and control theory, power systems, aerospace, and quantum systems. Various classical criteria include the Gram matrix criterion, Kalman rank criterion, and PBH test.

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Sub-manifold distance based object recognition in clutter

Sub-manifold distance based object recognition in clutter

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International Conference on Natural Computation

作者： Zhou, Hua Cai, Chao Ding, Mingyue National Lab for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Imaging Processing and Intelligence Control Key Laboratory of Education Ministry School of Life Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781424459612

Object recognition is challenging problem in computer vision due to appearance variation and presence of visual clutter and occlusions. Recently manifolds are thought to be fundamental for visual perception, and manifold learning algorithms are developed for discovering intrinsical features. Selective visual attention mechanism provides tools to reduce computation cost and avoid the influence of clutter background. In this paper, we described a new object recognition method, the submanifold distance (SMD) algorithm, which is induced by the visual attention mechanism to provide complex object recognition. Experiments with airport remote sensing images illustrated that our proposed algorithm can recognize complex objects accurately, robustly and quickly. ©2010 IEEE.

关键词： Object recognition

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Coverage control of multi-agent systems for ergodic exploration

Coverage control of multi-agent systems for ergodic explorat...

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第三十九届中国控制会议

作者： Zhulei Chen Li Xiao Qi Wang Zhuo Wang Zhigang Sun Key Laboratory of Imaging Processing and Intelligence Control School of Artificial Intelligence and AutomationHuazhong University of Science and Technology

In this paper,according to the ergodic theory,the ergodic metric is defined as the distance of the time average statistics of the agent's trajectories from the spatial distribution probability of the *** feedback control law of the agent's dynamic is designed using the ergodic metric to achieve uniform or non-uniform coverage of a given *** the same time,in order to expand the detection range,and obtain more complete and accurate environmental information and performed different types of tasks,the multi-agent system covers in the form of formation,and can adapt to move along the *** this paper,the combination of the leader-follower method and the artificial potential field method are used to control the formation of a multi-agent system.

关键词： ergodic theory area coverage multi-agent system leader-follower control artificial potential field

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Electrode localization in 3D Ultrasound images using 3D phase grouping and Randomized Hough transform

Electrode localization in 3D Ultrasound images using 3D phas...

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International Conference on Genetic and Evolutionary Computing

作者： Qiu, Wu Ding, Mingyue Yuchi, Ming School of Life Science and Technology Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9780769542812

A method to locate the axis of radio frequency ablation electrode(RFAE) in 3D Ultrasound(US) image is presented based on 3D phase-grouping in this paper. Firstly, all voxels in 3D US images are categorized into different groups which are called Line Support Region(LSR) according to the outer products of adjacent orientation vectors. And then, the RFAE axis is extracted with 3D Randomized Hough transform in the maximal LSR, instead of least squares fitting method;Finally, the endpoint of the RFAE axis is determined by searching along the axis with the probability distribution of voxels. The proposed method was tested in synthetic and 3D US agar phantom datas, the results are promising. © 2010 IEEE.

关键词： Hough transforms

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Knowledge-Data Fusion Based Source-Free Semi-Supervised Domain Adaptation for Seizure Subtype Classification

Knowledge-Data Fusion Based Source-Free Semi-Supervised Doma...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Peng, Ruimin An, Jiayu Wu, Dongrui School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control Wuhan430074 China

ISBN: (纸本)9781665410205

Electroencephalogram (EEG)-based seizure sub-type classification enhances clinical diagnosis efficiency. Source-free semi-supervised domain adaptation (SF-SSDA), which transfers a pre-trained model to a new dataset with no source data and limited labeled target data, can be used for privacy-preserving seizure subtype classification. This paper considers two challenges in SF-SSDA for EEG-based seizure subtype classification: 1) How to effectively fuse both raw EEG data and expert knowledge in classifier design? 2) How to align the source and target domain distributions for SF-SSDA? We propose a Knowledge-Data Fusion based SF-SSDA approach, KDF-MutuaISHOT, for EEG-based seizure subtype classification. In source model training, KDF uses Jensen-Shannon Diver-gence to facilitate mutual learning between a feature-driven Decision Tree-based model and a data-driven Transformer-based model. To adapt KDF to a new target dataset, an SF-SSDA algorithm, MutualSHOT, is developed, which features a consistency-based pseudo-label selection strategy. Experiments on the public TUSZ and CHSZ datasets demonstrated that KDF-MutualSHOT outperformed other supervised and source-free domain adaptation approaches in cross-subject seizure subtype classification. © 2024 IEEE.

关键词： Self-supervised learning

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