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A Scheme Library-Based Ant Colony Optimization with 2-Opt Local Search for Dynamic Traveling Salesman Problem

computer Modeling in Engineering & sciences 2023年第5期135卷 1209-1228页

作者： Chuan Wang Ruoyu Zhu Yi Jiang Weili Liu Sang-Woon Jeon Lin Sun Hua Wang College of Software Henan Normal UniversityXinxiang453007China College of Computer and Information Engineering Henan Normal UniversityXinxiang453007China School of Computer Science and Engineering South China University of TechnologyGuangzhou510006China School of Computer Science Guangdong Polytechnic Normal UniversityGuangzhou510665China Department of Military Information Engineering Hanyang UniversityAnsan15588South Korea College of Engineering and Science Institute for Sustainable Industries and Liveable CitiesVictoria UniversityMelbourneVIC 8001Australia

The dynamic traveling salesman problem(DTSP)is significant in logistics distribution in real-world applications in smart cities,but it is uncertain and difficult to *** paper proposes a scheme library-based ant colony optimization(ACO)with a two-optimization(2-opt)strategy to solve the DTSP *** work is novel and contributes to three aspects:problemmodel,optimization framework,and ***,in the problem model,traditional DTSP models often consider the change of travel distance between two nodes over time,while this paper focuses on a special DTSP model in that the node locations change dynamically over ***,in the optimization framework,the ACO algorithm is carried out in an offline optimization and online application framework to efficiently reuse the historical information to help fast respond to the dynamic *** framework of offline optimization and online application is proposed due to the fact that the environmental change inDTSPis caused by the change of node location,and therefore the newenvironment is somehowsimilar to certain previous *** way,in the offline optimization,the solutions for possible environmental changes are optimized in advance,and are stored in a mode scheme *** the online application,when an environmental change is detected,the candidate solutions stored in the mode scheme library are reused via ACO to improve search efficiency and reduce computational ***,in the algorithm design,the ACO cooperates with the 2-opt strategy to enhance search *** evaluate the performance of ACO with 2-opt,we design two challenging DTSP cases with up to 200 and 1379 nodes and compare them with other ACO and genetic *** experimental results show that ACO with 2-opt can solve the DTSPs effectively.

关键词： Dynamic traveling salesman problem(DTSP) offline optimization and online application ant colony optimization(ACO) two-optimization(2-opt)strategy

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Detail Recovery and Color Enhancement for Single Image Dehazing 11

Detail Recovery and Color Enhancement for Single Image Dehaz...

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11th International Conference on Networks, Communication and Computing, ICNCC 2022

作者： Fang, Wangming Huo, Zhanqiang Qiao, Yingxu School of Software Henan Polytechnic University Henan Jiaozuo454000 China School of Computer Science and Technology Henan Polytechnic University Henan Jiaozuo454000 China

ISBN: (纸本)9781450398039

Due to the complexity of taking photos on foggy days, images captured in the real world are prone to problems of detail loss, color dimness, and low saturation. Considering image dehazing as a problem of detail recovery and color enhancement, a two-stage progressive fusion method of single image dehazing is proposed, which consists of a detail recovery branch, a color enhancement branch, and a wavelet fusion module. Firstly, to solve the problem of hazy image details and detail loss after image defogging, we introduce gamma transform, block homomorphic filtering, and multi-scale exposure fusion in the detail recovery branch for the first fusion stage to restore image details. Secondly, aiming at the problem that the overall color of the image is dark and the image saturation is poor after defogging, the color-preserving CLAHE(limited contrast adaptive histogram equalization) of contrast enhancement method is applied in the color enhancement branch to enhance the color. Finally, to fully use the complementary information between the two enhanced images, a wavelet fusion module is designed for pixel-level fusion in the second stage, which can recover the details and improve color information while removing the fog to the greatest extent. The experimental results show that the image's color can be restored naturally, and the details can be preserved completely. The experimental results show that the image's color can be restored naturally and the details can be fully preserved. © 2022 ACM.

关键词： Color

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Mutual Retinex: Combining Transformer and CNN for Image Enhancement

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IEEE Transactions on Emerging Topics in Computational Intelligence 2024年第3期8卷 2240-2252页

作者： Jiang, Kui Wang, Qiong An, Zhaoyi Wang, Zheng Zhang, Cong Lin, Chia-Wen Harbin Institute of Technology School of Computer Science and Technology Harbin150001 China Wuhan University National Engineering Research Center for Multimedia Software School of Computer Science Wuhan430072 China Wuhan Polytechnic University School of Mathematics and Computer Science Wuhan430024 China National Tsing Hua University Department of Electrical Engineering Institute of Communications Engineering Hsinchu30013 Taiwan

Images captured in low-light or underwater environments are often accompanied by significant degradation, which can negatively impact the quality and performance of downstream tasks. While convolutional neural networks (CNNs) and Transformer architectures have made significant progress in computer vision tasks, there are few efforts to harmonize them into a more concise framework for enhancing such images. To this end, this study proposes to aggregate the individual capability of self-attention (SA) and CNNs for accurate perturbation removal while preserving background contents. Based on this, we carry forward a Retinex-based framework, dubbed as Mutual Retinex, where a two-branch structure is designed to characterize the specific knowledge of reflectance and illumination components while removing the perturbation. To maximize its potential, Mutual Retinex is equipped with a new mutual learning mechanism, involving an elaborately designed mutual representation module (MRM). In MRM, the complementary information between reflectance and illumination components are encoded and used to refine each other. Through the complementary learning via the mutual representation, the enhanced results generated by our model exhibit superior color consistency and naturalness. Extensive experiments have shown the significant superiority of our mutual learning based method over thirteen competitors on the low-light task and ten methods on the underwater image enhancement task. In particular, our proposed Mutual Retinex respectively surpasses the state-of-the-art method MIRNet-v2 by 0.90 dB and 2.46 dB in PSNR on the LOL 1000 and FIVEK datasets, while with only 19.8% model parameters. © 2017 IEEE.

关键词： Image enhancement

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Image Enhancement and Deep Learning in Predicting the Gleason Score of Transcrectal Ultrasound Images of Prostate Cancer 5

Image Enhancement and Deep Learning in Predicting the Gleaso...

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5th Asia-Pacific Conference on Image Processing, Electronics and computers, IPEC 2024

作者： Li, Xueri Liu, Zhiyong Yang, Lei Guangdong University of Science and Technology Department of Computer Science Dongguan China Guangdong Polytechnic Normal University School of computer science Guangzhou China

ISBN: (纸本)9798350374407

The Gleason grading system for prostate cancer offers a crucial point of reference for clinical evaluation of available treatment alternatives. However, there are few studies on pathological grading of prostate cancer ultrasound images, and how to accurately describe its aggressiveness is a hot issue. Therefore, this paper proposes a deep learning-based network model for Gleason grading of prostate cancer. The model consists of three modules: lesion region labelling, image enhancement, and pathological grading. Specifically, the model firstly uses the improved S-Mask R-CNN network model to label the prostate cancer lesion region, then performs image enhancement by morphological image processing and PCNN algorithm, and finally performs pathological grading of prostate ultrasound images using Xception. The experimental results on the prostate ultrasound image dataset collected in the hospital show that the prediction accuracy of the Gleason grading model in this paper is higher than that of other classical grading models and manual diagnosis by doctors. © 2024 IEEE.

关键词： Urology

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Research on Ultrasound Image Based Prostate Cancer Auxiliary Diagnosis System 5

Research on Ultrasound Image Based Prostate Cancer Auxiliary...

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5th Asia-Pacific Conference on Image Processing, Electronics and computers, IPEC 2024

作者： Li, Xueri Liu, Zhiyong Yang, Lei Guangdong University of Science and Technology College of Computer Science Dongguan China Guangdong Polytechnic Normal University School of computer science Guangzhou China

ISBN: (纸本)9798350374407

Image processing technology has made remarkable breakthroughs in recent years, driven by both algorithms and computing power. Not only has the image quality achieved a qualitative leap, but also its application in the fields of medical image diagnosis, security monitoring and analysis has become more and more extensive, providing a strong support for the scientific and technological progress of the society and the convenience of daily life. Currently, Prostate cancer ranks as one of the most frequently occurring malignant tumours, and the study of prostate cancer ultrasound image-assisted diagnosis artificial intelligence system helps accurate diagnosis and timely treatment. The improved Mask R-CNN is used to accurately segment the prostate region from the background in ultrasound images of the prostate;then the background information is masked and multiple prostate ultrasound image datasets are constructed for use in the Inception-V3 network for image classification and detection. Compared with other detection methods, this method has higher accuracy. This study will effectively improve the efficiency of prostate cancer diagnosis work. © 2024 IEEE.

关键词： Urology

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Heterologous Image Matching Based on Salience Region

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2025年第4期52卷 894-900页

作者： Zhai, Jinlong Xu, Yang Yan, Xiaohu Computer Science and Software Engineering University of Science and Technology LiaoNing Anshan114051 China School of Computer Science and Software Engineering University of Science and Technology LiaoNing Anshan114051 China Institute of Applied Artificial Intelligence of the Guangdong-Hong Kong-Macao Greater Bay Area Shenzhen Polytechnic University Shenzhen518055 China

To address the matching problem caused by the significant differences in spatial features, spectrum and contrast between heterologous images, a heterologous image matching method based on salience region is proposed in this paper. Firstly, texture features and corner features are detected. Secondly, the epanechnikov kernel function is used to calculate the point with the maximum kernel function value among all feature points, which is then defined as E-point. Thirdly, the salience region is defined and extracted according to the position of the E-point. Finally, six groups of heterologous images are used as data sources, and compared with HAPCG, HOWP, SIFT, and PSO_SIFT algorithms respectively. The results show that the comprehensive matching performance of the proposed method is better than the original algorithm without salience region processing. The root mean square error and the matching time are less than the original method while ensuring a similar number of matching points, which greatly improves the accuracy and speed of heterologous image matching. © (2025.0), (International Association of Engineers). All Rights Reserved.

关键词： Image matching

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Fuzzy PID Parameter Optimization of Hydraulic Turbine Based on Adaptive Hybrid Evolutionary Algorithm

Fuzzy PID Parameter Optimization of Hydraulic Turbine Based ...

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2024 International Conference on New Power System and Power Electronics, NPSPE 2024

作者： Li, Xueri Huang, Zhensheng Liu, Zhiyong Yang, Lei Guangdong University of Science and Technology Department of Computer Science Dongguan China Guangdong Polytechnic Normal University School of Computer Science Guangzhou China

ISBN: (纸本)9798350389869

Aiming at the optimization of PID parameters of hydropower units, based on the fuzzy PID controller, the characteristics of water turbine governing system and PID optimization index, the PID of hydro turbine governor is established Parameter optimization model: the self-adaptive hybrid evolution optimization algorithm framework (SAHEL) and fuzzy PID simulation test for 4% and 100% no-load frequency interference and 10% and 50% load frequency interference simulation test are adopted. Compared with traditional differential evolution, fuzzy differential evolution, particle swarm optimization and improved genetic algorithm, the fuzzy PID parameters obtained by the algorithm are compared under different working conditions (frequency disturbance or load disturbance), the number optimal solution not only has a small overshoot, but also has a short transition process time. ITAE index is also good, which is more conducive to the smooth, fast and stable system, and is more conducive to the theory and practice of parameter optimization of steam turbine governing system. © 2024 IEEE.

关键词： Genetic algorithms

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Hot-sim Supervised Contrastive Loss 2

Hot-sim Supervised Contrastive Loss

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2nd International Conference on Big Data, Artificial Intelligence and Risk Management, ICBAR 2022

作者： Chen, Wei Liu, Yiming Su, Bai shun Jiang, Tianjian School of Computer Science and Technology Henan Polytechnic University Jiaozuo China School of Computer Science and Technology Henan Polytechnic University Jiaozuo China School of Electrical and Information Engineering Hunan University Hunan China

ISBN: (纸本)9798350334265

In recent years, pretraining models using supervised contrastìve loss have defeated the crossentropy loss widely adopted to solve classification problems using deep learning. However, this approach is limited by its inability to directly train neural network models. To overcome this difficulty, we propose a novel loss function based on supervised contrastìve loss, which can directly train deep models. Our extensive evaluations of the CifarlO and the Mnist datasets show that our method achieves good performance on CifarlO and the Mnist datasets. © 2022 IEEE.

关键词： Deep learning

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An Enhanced Broad Learning System with Mean Time Series Difference for Aided Diagnosis of Mild Cognitive Impairment

An Enhanced Broad Learning System with Mean Time Series Diff...

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2024 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2024

作者： Wang, Jing He, Yong Jun Philip Chen, C.L. Jia, Xiping Lin, Zhiyong Zhao, Huiming School of Computer Science Guangdong Polytechnic Normal University Guangzhou China School of Computer Science & Engineering South China University of Technology Guangzhou China

ISBN: (纸本)9798350352788

Alzheimer's disease is a progressive neurological disorder. The disease is not reversible, but mild cognitive impairment is a transitional state between Alzheimer's disease and cognitively normal, it is a stage in which the brain is so minimally diseased that it can be treated or slowed or prevented from developing further lesions. At present, there are many methods for the aided diagnosis of mild cognitive impairment, among which the method based on fMRI medical images has emerged in recent years. However, the current aided diagnosis methods in this direction have some problems such as low accuracy and cumbersome feature extraction. A novel feature extraction method is put forward, namely the mean time series difference method in this paper. The feature extraction method effectively improves the accuracy in the auxiliary diagnosis task of mild cognitive impairment. An enhanced broad learning system with mean time series difference also was proposed. The results show that the enhanced broad learning system with mean time series can not only effectively optimize the feature extraction process, but also the accuracy of mild cognitive impairment classification tasks., which has significance for the clinical auxiliary diagnosis of mild cognitive impairment. © 2024 IEEE.

关键词： Contrastive Learning

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Image-assisted Label Connective Completion for Vessel Segmentation with Insufficient Annotations

Image-assisted Label Connective Completion for Vessel Segmen...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Zheng, Xiaoqi Yang, Baoyao Fang, Xiuwen Yao, Wenfang Ye, Mang School of Computer Science and Technology Guangdong University of Technology China School of Computer Science Wuhan University China School of Nursing The Hong Kong Polytechnic University Hong Kong

ISBN: (纸本)9798350368741

Automatic and accurate vessel segmentation is crucial for disease diagnosis. Deep learning methods are widely used, but their promising results rely on accurately annotated data. Due to complex vessel morphology and low-contrast image, accurate vessel delineation poses a practical challenge, resulting in insufficient annotations, which is a prominent form of noisy labels. This paper proposes an Image-assisted Label Connective Completion method, which enhances label's vessel information by images under the supervision of connectivity to address insufficient annotation issue. Specifically, we develop an Image-guided Vessel Enhancement module, which transmits structural information extracted from images based on label navigation to label space, promoting completion of missing annotated parts in original labels. In addition, a branch completion-connectivity loss is designed and introduced as an auxiliary supervision to prevent vessel branch disconnection during label completion. Experimental results on DRIVE, CHASE_DB1 and DCA1 datasets demonstrate that our method outperforms existing noisy labels learning methods. © 2025 IEEE.

关键词： Insufficient annotation Label completion Vessel segmentation

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