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IEEE Transactions on Artificial Intelligence 2024年第7期5卷 3431-3444页

作者： Deng, Lingfei Zhao, Changming Du, Zhenbang Xia, Kun Wu, Dongrui Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan 430074 China and also with Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen 518063 China

Semisupervised domain adaptation (SSDA) aims at training a high-performance model for a target domain using few labeled target data, many unlabeled target data, and plenty of auxiliary data from a source domain. Previous works in SSDA mainly focused on learning transferable representations across domains. However, it is difficult to find a feature space where the source and target domains share the same conditional probability distribution. Additionally, there is no flexible and effective strategy extending existing unsupervised domain adaptation (UDA) approaches to SSDA settings. In order to solve the above two challenges, we propose a novel fine-tuning framework, semisupervised transfer boosting (SS-TrBoosting). Given a well-trained deep learning-based UDA or SSDA model, we use it as the initial model, generate additional base learners by boosting, and then use all of them as an ensemble. More specifically, half of the base learners are generated by supervised domain adaptation, and half by semisupervised learning. Furthermore, for more efficient data transmission and better data privacy protection, we propose a source data generation approach to extend SS-TrBoosting to semisupervised source-free domain adaptation (SS-SFDA). Extensive experiments showed that SS-TrBoosting can be applied to a variety of existing UDA, SSDA, and SFDA approaches to further improve their performance. © 2020 IEEE.

关键词： Supervised learning

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Solving Nonlinear Equations Systems with a Two-Phase Root-Finder Based on Niching Differential Evolution 15th

Solving Nonlinear Equations Systems with a Two-Phase Root-Fi...

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15th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2020

作者： Duan, Lianlang Xu, Fei 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 Wuhan430074 China

ISBN: (纸本)9789811613531

Solving nonlinear equation systems (NESs) is a challenging problems in numerical computation. Two goals should be considered for solving NESs. One is to locate as many roots as possible and the other is to improve the solving precision. In this work, in order to achieve these two goals, a two-phase niching differential evolution (TPNDE) is proposed. The innovation of TPNDE is mainly reflected in the following three aspects. First, a probabilistic mutation mechanism is designed to increase the diversity of the population. Second, a novel reinitialization procedure is proposed to detect converged individuals and explore more new regions that may contain global optima. Third, distribution adjustment local search (DALS) is proposed to deal with the isolated solution and enhance the convergence of the algorithm. To evaluate the performance of TPNDE, we test our TPNDE and 5 state-of-the-art algorithms on 20 NESs with diverse features. The experimental results show that the proposed TPNDE algorithm is better than the other methods. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Nonlinear equations

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Improvement and invariance analysis of Zernike moments 1

Improvement and invariance analysis of Zernike moments

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1st International Conference on Communications, Circuits and Systems, ICCCAS 2002

作者： Bin, Ye Xiong, Peng Jia State Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology WuhanHubei430074 China

ISBN: (纸本)0780375475

An improved Zernike moment using a region-based shape descriptor is presented. The improved Zernike moment not only has rotation invariance, but also has scale invariance that the unimproved Zernike moment does not have. The experimental results show that the improved Zernike moment has better invariant properties than the unimproved Zernike moment using a region-based shape descriptor. © 2002 IEEE.

关键词： image enhancement

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Emotion Prediction in Conversation Based on Relationship Extraction

Emotion Prediction in Conversation Based on Relationship Ext...

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2022 IEEE International Conference on Cyborg and Bionic Systems, CBS 2022

作者： Yingjian, Liu Xiaoping, Wang Shanglin, Lei Huazhong University of Science and Technology School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China

ISBN: (纸本)9781665490283

With the development of human-computer interaction systems, emotion recognition in conversation (ERC) has attracted increasing interest in recent years. Motivated by recent studies which have proven that generating emotional conversation responses can effectively improve the performance of the ERC model. However, accurate emotional response is complicated due to the limited number of dialogue samples. Therefore, we propose a simple and effective framework for emotion prediction in conversation based on relationship extraction (DiaRP), consisting of two curricula: (1) Dialogue Relationship Capture (DRC);and (2) Next Emotion Prediction (NEP). In DRC, we capture the current emotional self-dependence and interpersonal dependence according to the influence of self and others on the current moment emotion in the conversation. We integrate self-dependence and interpersonal dependence for NEP to predict their emotional state without current utterance. We also measure the similarity between recognized emotion distribution and predicted emotion distribution by the KL divergence. With the proposed model-agnostic DiaRP strategy, we observe a significant performance improvement over a wide range of existing ERC models and achieve new state-of-the-art results on three public ERC datasets. © 2023 IEEE.

关键词： Emotion Recognition

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A New Scrambling Method Based on Semi-frequency Domain and Chaotic System

A New Scrambling Method Based on Semi-frequency Domain and C...

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2005 International Conference on Neural Networks and Brain(ICNN&B’05)

作者： Tao Li Shaowu Zhou Zhaofu Zeng Qingli Ou School of Information and Electrical Engineering Hunan University of Science and Technology Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science & Technology

ISBN: (纸本)0780394224

A new digital image scrambling method based on DCT and chaos maps is presented in this *** the chaotic system in semi-frequency domain,all the pixels of the original image are rearranged and *** procedure of the algorithm is roughly divided into three steps:first,an original image is decomposed for its first variable by 1-D DCT, then modulated by chaos system,a primary scrambling result is achieved,at last,after by inverse 1-D DCT for the scrambling result,repeating the same procedure for the second variable,a final scrambling result is obtained for the original *** confirm the robustness of the novel method,some robustness testing experiments are carried out on the scrambling *** experimental results shows that the method succeeds in enduring several kinds of common image attacks,such as cropping,noise and rotation.

关键词： image security image scrambling chaotic sequences DCT(the discrete cosine transform)

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Fast detection and symptom analysis of cracks in highway asphalt pavement

Fast detection and symptom analysis of cracks in highway asp...

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MIPPR 2009 - Pattern Recognition and Computer Vision: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Hong, Hanyu Zhang, Xiuhua Yu, Jiuyang Laboratory of Image Processing and Intelligent Control Wuhan Institute of Technology Wuhan 430074 China Institute for Technology Research and Innovation Deakin University VIC 3217 Australia

ISBN: (纸本)9780819478078

A method for real-time fast detection and symptom analysis of cracks in highway asphalt pavement is proposed. At the first step, the fissure characteristic of the acquired and de-noised pavement images is analyzed and then extracted by the method based on gray value comparison between the current pixel and its neighboring pixels, the false cracks are deleted by using the computed measurement of crack features, thus the true fissures are detected. The most important step is the symptom analysis of the cracks in the pavement image, all the data could be analyzed and be the basis for the agencies to remedy and manage the pavement. Quantities of images are processed and the results show that the proposed method can detect the pavement distress information actually, and has robustness and availability. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Feature extraction

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Cortical Neural P Systems 15th

Cortical Neural P Systems

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15th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2020

作者： Fu, Zhongzheng Zhang, Luping 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 Wuhan430074 China

ISBN: (纸本)9789811613531

P systems are distributed and parallel computing models inspired from living cells. In this work, a variant of spiking neural P systems, cortical neural P systems, are proposed in the frame work of P systems combining the topology structure of basic P system and information processing style in spiking neurons. The computational power of cortical neural P systems is investigated. It is proved that cortical neural P systems are equivalent to Turing machines as number generators. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Turing machines

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A fast quantum mechanics based contour extraction algorithm

A fast quantum mechanics based contour extraction algorithm

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Medical Imaging 2009 - image processing

作者： Lan, Tian Sun, Yangguang Ding, Mingyue Institute for Pattern Recognition and Artificial Intelligence Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819475107

A fast algorithm was proposed to decrease the computational cost of the contour extraction approach based on quantum mechanics. The contour extraction approach based on quantum mechanics is a novel method proposed recently by us, which will be presented on the same conference by another paper of us titled "a statistical approach to contour extraction based on quantum mechanics". In our approach, contour extraction was modeled as the locus of a moving particle described by quantum mechanics, which is obtained by the most probable locus of the particle simulated in a large number of iterations. In quantum mechanics, the probability that a particle appears at a point is equivalent to the square amplitude of the wave function. Furthermore, the expression of the wave function can be derived from digital images, making the probability of the locus of a particle available. We employed the Markov Chain Monte Carlo (MCMC) method to estimate the square amplitude of the wave function. Finally, our fast quantum mechanics based contour extraction algorithm (referred as our fast algorithm hereafter) was evaluated by a number of different images including synthetic and medical images. It was demonstrated that our fast algorithm can achieve significant improvements in accuracy and robustness compared with the well-known state-of-the-art contour extraction techniques and dramatic reduction of time complexity compared to the statistical approach to contour extraction based on quantum mechanics. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Wave functions

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Double recursive algorithm based on fuzzy entropy for image thresholding

Double recursive algorithm based on fuzzy entropy for image ...

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MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Zhang, Xiuhua Hong, Hanyu Laboratory of Image Processing and Intelligent Control Wuhan Institute of Technology Wuhan 430074 China Institute for Technology Research and Innovation Deakin University VIC 3217 Australia

ISBN: (纸本)9780819478085

A double recursive algorithm based on fuzzy entropy for image thresholding is proposed. The inner recursive step is to calculate the threshold between the given gray level interval, and the outer recursive step is to calculate the optimal for the image with small objects. Experiments on steel billet image show that the proposed algorithm can threshold image fast and exactly, which has effectiveness and application for real time image segmentation. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： image segmentation

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Representative Graph Neural Network 16th

Representative Graph Neural Network

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16th European Conference on Computer Vision, ECCV 2020

作者： Yu, Changqian Liu, Yifan Gao, Changxin Shen, Chunhua Sang, Nong Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China The University of Adelaide Adelaide Australia

ISBN: (纸本)9783030585709

Non-local operation is widely explored to model the long-range dependencies. However, the redundant computation in this operation leads to a prohibitive complexity. In this paper, we present a Representative Graph (RepGraph) layer to dynamically sample a few representative features, which dramatically reduces redundancy. Instead of propagating the messages from all positions, our RepGraph layer computes the response of one node merely with a few representative nodes. The locations of representative nodes come from a learned spatial offset matrix. The RepGraph layer is flexible to integrate into many visual architectures and combine with other operations. With the application of semantic segmentation, without any bells and whistles, our RepGraph network can compete or perform favourably against the state-of-the-art methods on three challenging benchmarks: ADE20K, Cityscapes, and PASCAL-Context datasets. In the task of object detection, our RepGraph layer can also improve the performance on the COCO dataset compared to the non-local operation. Code is available at https://***/RepGraph. © 2020, Springer Nature Switzerland AG.

关键词： Semantic Segmentation

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