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第41届中国控制会议

作者： Yunong Zhang Zhiwen Yuan School of Computer Science and Engineering Sun Yat-sen University Guangdong Key Laboratory of Modern Control Technology Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education Research Institute of Sun Yat-sen University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper presents three relatively effective numerical algorithms,i.e.,94 LVI algorithms of OIpU(one-iteration-perupdate) type,to handle time-dependent QP(quadratic programming) problems subject to two constraints respectively(i.e.,equality and inequality constraints,equality and bound constraints,or inequality and bound constraints).Specifically,two "bridges" play essential parts of the methods(i.e.,the first "bridge" makes a QP problem convert to an LVI [linear variational inequality],and the second "bridge" makes the LVI convert to a PLPE [piecewise-linear projection equation]).On the basis of the standard94 LVI algorithm,the methods only update once through the solution of the previous sampling time ***,we conduct a number of experiments to substantiate the three algorithms respectively,which use exponential functions,log functions,and trigonometric functions in corresponding coefficients of the experimental examples.

关键词： Quadratic programming Time-dependent Numerical algorithms Linear variational inequalities(LVI)

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Class-specific Prompts in Vision Transformer for Continual Learning of New Diseases

Class-specific Prompts in Vision Transformer for Continual L...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Zhao, Defeng Ye, Zejun Zheng, Wei-Shi Wang, Ruixuan Sun Yat-sen University School of Computer Science and Engineering Guangzhou China Peng Cheng Laboratory Department of Network Intelligence Shenzhen China Moe Key Laboratory of Machine Intelligence and Advanced Computing China

ISBN: (纸本)9798350337488

Current intelligent diagnosis systems are often trained to diagnose a small number of diseases and lack the ability of continually learning new disease knowledge. To have such continual learning ability, the deployed intelligent system needs to be continually updated based on training data of only new diseases, without accessing old data of previously learned diseases due to privacy concerns and challenges in data sharing across medical centers. In this study, a novel and effective prompt learning strategy is proposed to help a pretrained and fixed Vision Transformer (ViT) continually learn new diseases. In particular, a set of unique prompts for each disease are effectively learned such that discriminative disease features can be well extracted from the fixed ViT under the instructions of prompts during feature extraction, even though the ViT feature extractor is pretrained in the natural image domain. Extensive empirical evaluations on two medical image datasets and one natural image dataset demonstrate the superior performance of the proposed method. The source code is available at https://***/zhaoedf/CSPrompt. © 2023 IEEE.

关键词： Continual learning Disease diagnosis Prompt learning

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Inequality-Type Zhang Equivalency of Great-Than-or-Equal-to (GTOET) Sign in Matrix-Vector,Matrix,and Integral Situations Applied to Obstacle Avoidance 41

Inequality-Type Zhang Equivalency of Great-Than-or-Equal-to ...

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第41届中国控制会议

作者： Yunong Zhang Jianzhen Xiao School of Computer Science and Engineering Sun Yat-sen University Research Institute of Sun Yat-sen University in Shenzhen Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In this paper,the concept of Zhang equivalency(ZE) and equality-type ZE are *** the basis of equalitytype ZE,we introduce the inequality-type ZE of great-than-or-equal-to(GTOET) sign and thus propose the order-1,order-2,and order-3 general formulas of the inequality-type ZE of GTOET ***,we investigate the inequality-type ZE of GTOET sign in three different and appealing situations,including matrix-vector situation,matrix situation,and integral ***,the corresponding formulas are *** distance between a certain object and an obstacle can be considered as the point-to-point distance,and thus the obstacle avoidance scheme is described as an *** by that thought,we apply the inequality-type ZE of GTOET sign to the matrix-form obstacle avoidance.

关键词： Zhang equivalency Great-than-or-equal-to(GTOET) sign Inequalities Obstacle avoidance

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Solving Multitrip Pickup and Delivery Problem With Time Windows and Manpower Planning Using Multiobjective Algorithms

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IEEE/CAA Journal of Automatica Sinica 2020年第4期7卷 1134-1153页

作者： Jiahai Wang Yuyan Sun Zizhen Zhang Shangce Gao the Department of Computer Science and also with the Key Laboratory of Machine Intelligence and Advanced ComputingMinistry of Educationand also with the Guangdong Key Laboratory of Big Data Analysis and ProcessingSun Yat-sen UniversityGuangzhou 510275China the Department of Computer Science Sun Yat-sen UniversityGuangzhou 510275China the Faculty of Engineering University of ToyamaToyama-shi 930-8555Japan

The multitrip pickup and delivery problem with time windows and manpower planning(MTPDPTW-MP)determines a set of ambulance routes and finds staff assignment for a hospital. It involves different stakeholders with diverse interests and objectives. This study firstly introduces a multiobjective MTPDPTW-MP(MO-MTPDPTWMP) with three objectives to better describe the real-world scenario. A multiobjective iterated local search algorithm with adaptive neighborhood selection(MOILS-ANS) is proposed to solve the problem. MOILS-ANS can generate a diverse set of alternative solutions for decision makers to meet their requirements. To better explore the search space, problem-specific neighborhood structures and an adaptive neighborhood selection strategy are carefully designed in MOILS-ANS. Experimental results show that the proposed MOILS-ANS significantly outperforms the other two multiobjective algorithms. Besides, the nature of objective functions and the properties of the problem are analyzed. Finally, the proposed MOILS-ANS is compared with the previous single-objective algorithm and the benefits of multiobjective optimization are discussed.

关键词： Adaptive neighborhood selection manpower planning multiobjective optimization multitrip pickup and delivery problem with time windows

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Contour-guided person re-identification 2nd

Contour-guided person re-identification

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

作者： Chen, Jiaxing Yang, Qize Meng, Jingke Zheng, Wei-Shi Lai, Jian-Huang School of Data and Computer Science Sun Yat-sen University Guangzhou China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education Beijing China

ISBN: (纸本)9783030317256

Feature representation is one of the crucial components in person re-identificationre-ID. Recently, local feature has attracted great attention from the re-ID community, and extra visual cues have been well exploited to guide local feature learning, such as pose cues, semantic parsing and etc. Besides, the latest research demonstrates that general CNN-based deep models have a bias to texture feature in pattern recognition, but ignore shape-based feature, which has been verified as significant for cross-domain invariance. As far as we know, there is little work focusing on shape-based feature on person re-ID. In this paper, we introduce a new data modality, pedestrian contour, into the re-ID community, which to our best knowledge is the first attempt to utilize contour explicitly in deep re-ID models. We hypothesize that, as an alternative of other exploited visual cues, pedestrian contour could guide deep models to learn robust shape-based feature, with build-in prior information. We propose several contour-guided architectures to explicitly use pedestrian contour, including plain ones and multi-scale one. Extensive experiments have validated the effectiveness of our models. Moreover, we transfer the methodology into a powerful part-based model, Part-based Convolutional BaselinePCB, and boost the model performance, which verifies the promising prospect of contour-guided models to expand as an auxiliary mechanism in re-ID. © Springer Nature Switzerland AG 2019.

关键词： Semantics

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Learning High-Performance Spiking Neural Networks with Multi-Compartment Spiking Neurons 12th

Learning High-Performance Spiking Neural Networks with Mult...

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12th International Conference on Image and Graphics, ICIG 2023

作者： Li, Xinjie Tang, Jianxiong Lai, Jianhuang School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education Guangzhou China

ISBN: (纸本)9783031463075

In recent years, spiking neural networks (SNNs) have gained significant attention due to bio-inspired working mechanism. The VGG-like and ResNet-like architectures are widely used for SNNs modeling. However, the spiking features of such architectures are generated by the layer-wise Integrate-and-Fire (IF) dynamics. The firing of deep neurons is independent of the neurons in the shallow layers. In this paper, we propose Multi-Compartment Spiking Neural Network (MC-SNN) that integrates the MPs of the shallow neurons to fire the deep neurons. Specifically, the MC-SNN is modeled by a Multi-Compartment Leaky Integrate-and-Fire (MC-LIF) neuron and an Adaptive Gating Unit (AGU). The MC-LIF neuron models the IF dynamics using the MPs from both deep and shallow layers, and the AGU adaptively scales the MPs of the MC-LIF neuron. These increase the information interaction between spiking neurons and improve the performance of SNNs. Besides, we design the Binarized Synaptic Encoder (BSE) to reduce the computation cost for the input of SNNs. Experimental results show that the MC-SNN performs well on the neuromorphic datasets, reaching 79.52% and 81.24% on CIFAR10-DVS and N-Caltech101, respectively. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Neurons

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Gecnn-crf for prostate cancer detection with wsi

Gecnn-crf for prostate cancer detection with wsi

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Chinese Intelligent Systems Conference, CISC 2020

作者： Dong, Jinfeng Guo, Xuemei Wang, Guoli School of Data and Computer Science Sun Yat-sen University Guangzhou China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education Guangzhou China

ISBN: (纸本)9789811584497

Pathological examination is of great significance for the diagnosis and treatment of prostate cancer, but artificial pathological examination is time-consuming, laborious and error prone. Automatic pathological examination can assist doctors in diagnosis and treatment. In this paper, a deep learning convolution network based on group equivariant convolution and conditional random field is proposed, which solves the problem of inconsistent features of data after random rotation in the learning process and enhances the robustness of the network. On the other hand, the conditional random field method is used to produce the same result on the slice image, which makes the segmentation edge of the probability image clearer. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021.

关键词： Convolution

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Halftone Image Steganography with Distortion Measurement Based on Structural Similarity 18th

Halftone Image Steganography with Distortion Measurement Bas...

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18th International Workshop on Digital Forensics and Watermarking, IWDW 2019

作者： Liu, Wanteng Yin, Xiaolin Lu, Wei Zhang, Junhong School of Data and Computer Science Guangdong Key Laboratory of Information Security Technology Ministry of Education Key Laboratory of Machine Intelligence and Advanced Computing Sun Yat-sen University Guangzhou510006 China

ISBN: (纸本)9783030435745

For halftone image data hiding, it is difficult to achieve good visual quality and statistical security when high embedding capacity is demanded. In this paper, a secure steganographic scheme for halftone image is proposed, which aims to minimize the embedding distortion on structural similarity. Structural distortions are the ones that affect the most the perception of degradation of a halftone image. To evaluate the structural distortions caused by flipping pixels, halftone image structural similarity (HSSIM) is introduced based on a human visual filter, which is trained by Least-Mean-Square (LMS) approach. Utilizing the HSSIM, a distortion measurement is proposed to evaluate the embedding distortions on both vision and statistics. To minimize the embedding distortions, syndrome-trellis code (STC) is employed in the embedding process. The experimental results have demonstrated that the proposed steganographic scheme can achieve high statistical security with good visual quality without degrading the embedding capacity. © 2020, Springer Nature Switzerland AG.

关键词： Steganography

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VISUALLY MAINTAINED IMAGE DISTURBANCE AGAINST DEEPFAKE FACE SWAPPING

VISUALLY MAINTAINED IMAGE DISTURBANCE AGAINST DEEPFAKE FACE ...

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2021 IEEE International Conference on Multimedia and Expo, ICME 2021

作者： Dong, Junhao Xie, Xiaohua School of Computer Science and Engineering Sun Yat-sen University China Guangdong Key Laboratory of Information Security Technology China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education China

ISBN: (纸本)9781665438643

As a deep learning-based application, DeepFake can generate malicious images or videos through replacing the face of a source image with the target face, which poses a significant threat to social media. In this paper, we propose a scheme to prevent such tampering by exploring adversarial examples against DeepFake. Specifically, adversarial examples are produced by adding tailored distortion to source images. The added distortion is imperceptible to human vision but can mislead the generation of face-swapped images effectively. We present three novel adversarial attacks against DeepFake autoencoders from perspectives of adversarial transferability and latent representation. Our first method synthesizes universal perturbation, which is image-agnostic. By contrast, the latter two methods directly perform the preciser perturbation specific to a source image. Extensive experiments demonstrate the effectiveness of our adversarial examples against DeepFake in terms of both reference and non-reference image quality assessment. © 2021 IEEE

关键词： Deep learning

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Design and Validation of a Hyper-converged Blockchain Hardware and Software System Based on Domestic Chips 1st

Design and Validation of a Hyper-converged Blockchain Hardwa...

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1st Conference on Blockchain and Web3.0 Technology Innovation and Application, BWTAC 2024

作者： Liu, Xiaolong Yuan, Bo Wu, Faguo Enterprise Technology Center Aerospace Legione Technology Co. Ltd Haidian Beijing100195 China School of Computer Science and Engineering Beihang University Haidian Beijing100191 China State Key Laboratory of Software Development Environment Beihang University Haidian Beijing100191 China Institute of Artificial Intelligence Beihang University Haidian Beijing100191 China Beihang University Haidian Beijing100191 China Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing Beihang University Haidian Beijing100191 China

ISBN: (纸本)9789819794119

This paper proposes a hyper-converged blockchain hardware and software sys-tem based on domestic chips. By utilizing domestically firmware, the Linux operating system, X86 architecture Hygon processors, and ARM architecture Phytium processors, combined with servers, storage, network, and independently controllable blockchain technologies, the system achieves integrated hardware and software optimization. This significantly improves performance and scalability. Experimental results demonstrate that the system performs excellently in various high-security application scenarios, providing reliable solutions for government, finance, taxation, transportation, energy, and telecommunications sectors. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Firmware

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