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New Trends in Computational Intelligence (NTCI), International Conference on

作者： Liangjin Diao Longfeng Shen Jiacong Chen Fangzhen Ge Mengwen Li Anhui Engineering Research Center for Intelligent Computing and Application on Cognitive Behavior (ICACB) College of Computer Science and Technology Huaibei Normal University Huaibei Anhui China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei China Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei Anhui China

ISBN: (数字)9798331517021

ISBN: (纸本)9798331517038

Recent advancements in CNNs for medical image segmentation have focused on the combination of CNN and Transformer architectures to capture both local and global features. However, challenges remain, such as effectively utilizing fused features at the encoder-decoder bottleneck and addressing blurred object edges in datasets. To tackle these issues, we introduce a multi-scale channel adaptive sensing module, enhancing the model's representational and perceptual capabilities by integrating multi-scale and channel-specific information. Additionally, we propose a cross-perception module and multi-scale segmentation head to improve global coordination and multi-scale information gathering. Experiments on the ACDC and Synapse datasets demonstrate our model's superiority.

关键词： Image segmentation Adaptation models Head Image edge detection Computer architecture Transformers Market research Sensors Synapses Biomedical imaging

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Detection of Children’s Molars Based on Noise Filter

Research Square

引用

Research Square 2022年

作者： Yan, Zhiwen Chen, Ying Song, Jinlong Zhu, Jia Li, Jianbo School of Computing Science South China Normal University Guangzhou China Key Laboratory of Intelligent Education Technology Application of Zhejiang Province Zhejiang Normal University Zhejiang China Stomatological Hospital Southern Medical University Guangzhou China

Pit and fissure sealant is for children aged seven to twelve years to prevent molars from becoming caries. In this paper, we propose a new detection framework to identify whether children need pit and fissure sealing. We divide the framework into two parts: molar detection and molar classification. According to the characteristics of teeth, we propose to use the clustering method to filter the bounding box in the object detection part. In the region divided by clustering, we only keep one detection frame in the same category. In the classification part, we propose a noise filtering layer based on wavelet transform for feature extraction. We map the training samples to another space in the training process based on metric learning to increase the distance between categories and improve the accuracy of classification. © 2022, CC BY.

关键词： Wavelet transforms

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How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing 41

How Universal Polynomial Bases Enhance Spectral Graph Neural...

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41st International Conference on Machine Learning, ICML 2024

作者： Huang, Keke Wang, Yu Guang Li, Ming Liò, Pietro School of Computing National University of Singapore Singapore Institute of Natural Sciences School of Mathematical Sciences Zhangjiang Institute for Advanced Study Shanghai Jiao Tong University Shanghai China Shanghai AI Laboratory Shanghai China School of Mathematics and Statistics University of New South Wales Sydney Australia Zhejiang Institute of Optoelectronics Jinhua China Zhejiang Key Laboratory of Intelligent Education Technology and Application Zhejiang Normal University Jinhua China Department of Computer Science and Technology Cambridge University Cambridge United Kingdom

Spectral Graph Neural Networks (GNNs), alternatively known as graph filters, have gained increasing prevalence for heterophily graphs. Optimal graph filters rely on Laplacian eigendecomposition for Fourier transform. In an attempt to avert prohibitive computations, numerous polynomial filters have been proposed. However, polynomials in the majority of these filters are predefined and remain fixed across different graphs, failing to accommodate the varying degrees of heterophily. Addressing this gap, we demystify the intrinsic correlation between the spectral property of desired polynomial bases and the heterophily degrees via thorough theoretical analyses. Subsequently, we develop a novel adaptive heterophily basis wherein the basis vectors mutually form angles reflecting the heterophily degree of the graph. We integrate this heterophily basis with the homophily basis to construct a universal polynomial basis UniBasis, which devises a polynomial filter-based graph neural network - UniFilter. It optimizes the convolution and propagation in GNN, thus effectively limiting over-smoothing and alleviating over-squashing. Our extensive experiments, conducted on datasets with a diverse range of heterophily, support the superiority of UniBasis in the universality but also its proficiency in graph explanation. Copyright 2024 by the author(s)

关键词： Wiener filtering

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RIESZ TYPE THEOREMS FOR κ-PLURIHARMONIC MAPPINGS, INVARIANT HARMONIC QUASIREGULAR MAPPINGS AND HARMONIC QUASIREGULAR MAPPINGS

arXiv

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arXiv 2023年

作者： Chen, Shaolin Huang, Manzi College of Mathematics and Statistics Hengyang Normal University Hunan Hengyang421002 China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application 421002 China Key Laboratory of High Performance Computing and Stochastic Information Processing College of Mathematics and Statistics Hunan Normal University Hunan Changsha410081 China

The main purpose of this paper is to develop some methods to improve and generalize the main results in a recent paper by Liu and Zhu (Adv. Math., 2023, i.e., [19]). The paper consists of two parts. In the first part, we discuss the Riesz type theorem in the setting of n-dimensional complex spaces for all n ≥ 1. In this part, we first introduce the family of κ-pluriharmonic mappings of the n-dimensional complex unit ball. Then we establish two Riesz type theorems for these mappings, which are the n-dimensional versions of Theorems 1.1 and 1.2 in [19], respectively. Furthermore, even when n = 1, our first result shows that the assumption of the real parts of the mappings not being negative (or being negative) in [19, Theorem 1.1] is redundant;and our second result illustrates that the assumption of "quasiconformality" on the mappings in [19, Theorem 1.2] can be replaced by the weaker one of "quasiregularity". In the second part, we investigate the Riesz type theorem in the setting of n-dimensional real spaces for all n ≥ 2. In this part, first, we prove a Riesz type theorem for invariant harmonic quasiregular mappings of the unit n-dimensional real ball. Our result indicates that (i) the range of the parameter p discussed in [19, Theorem 1.3] can be changed from (1, 2) to (1, ∞);(ii) the assumption of the first coordinate functions of the mappings being non-zero in [19, Theorem 1.3] is redundant. In this way, we complete the discussions carried out in [19, Theorems 1.3 and 1.4]. Second, we obtain a Riesz type theorem for harmonic K-quasiregular mappings of the unit n-dimensional real ball. Our result demonstrates that the range of the parameter p discussed in [15, Theorem 2.1] can be changed from (1, 2) to (1, ∞).MSC Codes 30H10, 30C62 Copyright © 2023, The Authors. All rights reserved.

关键词： Harmonic analysis

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UJN-Land: A Large-Scale High-Resolution Parcel of Land of Multi-temporal Dataset with CNN Based Semantic Segmentation Analysis 7th

UJN-Land: A Large-Scale High-Resolution Parcel of Land of Mu...

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7th International Conference on Life System Modeling and Simulation, LSMS 2021, and the 7th International Conference on intelligent computing for Sustainable Energy and Environment, ICSEE 2021

作者： Shen, Yuan Wang, Yulin Yang, Shiyong Li, Yan Han, Shiyuan Liu, Zhen Xu, Tao School of Information Science and Engineering University of Jinan Jinan250022 China Highresolution Earth Observation System Shandong Center of Data and Application University of Jinan Jinan250022 China Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan Jinan250022 China Shandong Institutes of Industrial Technonlogy Jinan250102 China Land Spatial Data and Remote Sensing Technology Institute of Shandong Province Jinan250002 China

ISBN: (纸本)9789811672125

Semantic segmentation of land in remote sensing images plays an important role in urban management and rural planning, and can provide intelligent analysis for urban development. Convolutional neural network (CNN) based methods have achieved good performance in object detection in computer vision, which benefits from the popularity of large-scale datasets. However, most of segmentation of land dataset were constructed based on various satellite images and samples that lack the number and diversity of existing datasets. These problems have brought challenges to the improvement and application of CNN based land parcel segmentation methods. This paper presented a large-scale high-resolution land dataset based on CNN analysis. More than 200,000 images of 256*256 pixels were obtained from Gaofen satellite images with a spatial resolution of 0.8 m, in which four category samples were manually annotated. In the experiment, three CNN based semantic segmentation methods were used as experimental baseline methods. The experimental results showed that the availability of the UJN-Land dataset is beneficial to the planning and management of cultivated land. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Semantic Segmentation

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A DECOUPLED STRUCTURE PRESERVING SCHEME FOR THE POISSON-NERNST-PLANCK NAVIER-STOKES EQUATIONS AND ITS ERROR ANALYSIS

arXiv

引用

arXiv 2023年

作者： Yu, Ziyao Cheng, Qing Shen, Jie Wang, Changyou Department of Mathematics West LafayetteIN47907 United States Key Laboratory of Intelligent Computing and Application Tongji University Ministry of Education Department of Mathematics Tongji University Shanghai200092 China Eastern Institute of Technology Zhejiang Ningbo315200 China

We consider in this paper a numerical approximation of Poisson-Nernst-Planck-Navier-Stokes (PNP-NS) system. We construct a decoupled semi-discrete and fully discrete scheme that enjoys the properties of positivity preserving, mass conserving, and unconditionally energy stability. Then, we establish the well-posedness and regularity for the initial and (periodic) boundary value problem of the PNP-NS system under suitable assumptions on the initial data, and carry out a rigorous convergence analysis for the fully discretized scheme. We also present some numerical results to validate the positivity preserving property and the accuracy of our scheme. Copyright © 2023, The Authors. All rights reserved.

关键词： Navier Stokes equations

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Efficient and Sustainable Battery-Swap Service for On-Demand Food Delivery Platform: An Aiot-Based System

SSRN

引用

SSRN 2023年

作者： Liu, Xuanwu Li, Zhao Zhang, Jiarun Li, Ming Ren, Guoqi Huang, Jiaming Zhang, Ji Hangzhou Yugu Technology Co. Ltd. Hangzhou China Key Laboratory of Intelligent Education Technology Application of Zhejiang Province Zhejiang Normal University Jinhua China School of Mathematics Physics and Computing University of Southern Queensland Toowoomba Australia

The food delivery industry has undergone significant growth in recent years, providing a large number of jobs globally through on-demand delivery services. In densely populated areas, such as major cities in China, food delivery workers prefer electric bicycles over cars to achieve the highest delivery efficiency while minimizing their costs. However, battery volume limitations force riders to charge the batteries during work to fulfill their work intensity, which often results in wasted time and mileage as riders travel back home for a battery swap or recharge. To address this issue, we have proposed the Battery-swap System as an On-demand delivery service (BaaS), an intelligent IoT-based charging and swapping system that integrates end-cloud collaboration, safety detection, and energy consumption management technologies. BaaS enables efficient battery swapping services to replace battery charging, enabling riders to swap depleted batteries at convenient locations, thereby reducing the time and mileage wasted on traveling home for recharging. Our BaaS has been implemented in over 50 major cities in China, serving almost a million customers, and saving about 15 million kWh of electricity, while reducing approximately 0.7 billion invalid mileage. Despite BaaS’s positive impact on the environment and society, there is a lack of methods and metrics to measure its effect. Therefore, in this paper, we propose a Valid Distance Estimation Model (VDEM) to measure the environmental and social impact of BaaS based only on the daily user logs of BaaS. VDEM collects daily usage logs from our cloud center, processes the user logs to create a new database, and uses two hypotheses to estimate the impact of BaaS based on invalid mileages and order numbers. We further design experiments to demonstrate the effectiveness of BaaS. The results indicate that BaaS prevents delivery riders from losing approximately 40% of orders, demonstrating its significant potential in fields such as en

关键词： Internet of things

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Efficient and Sustainable Battery-Swap Service for On-Demand Food Delivery Platform: An Aiot-Based System

SSRN

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SSRN 2023年

关键词： Internet of things

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Fer-Chc: Facial Expression Recognition with Cross-Hierarchy Contrast

SSRN

引用

SSRN 2022年

作者： Wu, Xuemei He, Jie Huang, Changqin Huang, Qionghao Zhu, Jia Huang, Xiaodi Fujita, Hamido Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province Zhejiang Normal University Jinhua321004 China School of Computing Mathematics and Engineering Charles Sturt University NSW Australia Software and Information Science Iwate Prefectural University Takizawa020-0693 Japan

Remarkable progress has been made in facial expression recognition (FER) tasks with convolutional neural networks (CNNs). However, these CNN-based approaches do not well capture the detailed and crucial features that can distinguish different facial expressions from a global perspective among multiple facial expressions. The performance of existing CNN-based models for FER is still much room for improvement. As such, we propose a novel cross-hierarchy contrast (CHC) framework named FER-CHC for facial expression recognition tasks. The basic idea of FER-CHC is to employ a CHC to regularize the feature learning of the backbone network and enhance global representations of facial expressions. Specifically, the CHC captures common and differential features from different facial expressions with a cross-hierarchy contrast mechanism. The fusion network globally integrates the features learned from a backbone network and CHC to learn a more robust feature representation. Comprehensive experiments were conducted on six popular datasets: CK+, FER2013, FER+, RAF-DB, AffectNet, and JAFFE. The results show that our proposed FER-CHC achieves state-of-the-art performances on these datasets. In addition, the ablation study also demonstrates the effectiveness of the proposed components in FER-CHC. © 2022, The Authors. All rights reserved.

关键词： Convolutional neural networks

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A Reference Vector-Assisted Many-Objective Optimization Algorithm with Adaptive Niche Dominance Relation

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intelligent Automation & Soft computing 2024年第2期39卷 189-211页

作者： Fangzhen Ge Yating Wu Debao Chen Longfeng Shen School of Computer Science and Technology Huaibei Normal UniversityHuaibei340604China School of Physic and Electronic Information Huaibei Normal UniversityHuaibei340604China Anhui Engineering Research Center for Intelligent Computing and Application on Cognitive Behavior(ICACB) Huaibei Normal UniversityHuaibei340604China Anhui Province Key Laboratory of Intelligent Computing and Applications Huaibei Normal UniversityHuaibei340604China Institute of Artificial Intelligence Hefei Comprehensive National Science CenterHefei230000China

It is still a huge challenge for traditional Pareto-dominatedmany-objective optimization algorithms to solve manyobjective optimization problems because these algorithms hardly maintain the balance between convergence and diversity and can only find a group of solutions focused on a small area on the Pareto front,resulting in poor performance of those *** this reason,we propose a reference vector-assisted algorithmwith an adaptive niche dominance relation,for short *** new dominance relation forms a niche based on the angle between candidate *** comparing these solutions,the solutionwith the best convergence is found to be the non-dominated solution to improve the selection *** reproduction,a mutation strategy of k-bit crossover and hybrid mutation is used to generate high-quality *** 23 test problems with up to 15-objective,we compared the proposed algorithm with five state-of-the-art *** experimental results verified that the proposed algorithm is competitive.

关键词： Many-objective optimization evolutionary algorithm Pareto dominance reference vector adaptive niche

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