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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Zhong, Haixin Huang, Mingyi Dai, Wei P. Wang, Haoyu Roe, Anna Wang Yu, Yuguo Research Institute of Intelligent Complex Systems Fudan University China State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science Institutes of Brain Science Fudan University China Institute of Science and Technology for Brain-Inspired Intelligence Fudan University China MOE Frontier Science Center for Brain Science and Brain-machine Integration School of Brain Science and Brain Medicine Key Laboratory of Biomedical Engineering of Ministry of Education College of Biomedical Engineering and Instrument Science Zhejiang University China Shanghai Artificial Intelligence Laboratory China

During natural evolution, the primary visual cortex (V1) of lower mammals typically forms salt-and-pepper organizations, while higher mammals and primates develop pinwheel structures with distinct topological properties. Despite the general belief that V1 neurons primarily serve as edge detectors, the functional advantages of pinwheel structures over salt-and-peppers are not well recognized. To this end, we propose a two-dimensional self-evolving spiking neural network that integrates Hebbian-like plasticity and empirical morphological data. Through extensive exposure to image data, our network evolves from salt-and-peppers to pinwheel structures, with neurons becoming localized bandpass filters responsive to various orientations. This transformation is accompanied by an increase in visual field overlap. Our findings indicate that neurons in pinwheel centers (PCs) respond more effectively to complex spatial textures in natural images, exhibiting quicker responses than those in salt-and-pepper organizations. PCs act as first-order stage processors with heightened sensitivity and reduced latency to intricate contours, while adjacent iso-orientation domains serve as second-order stage processors that refine edge representations for clearer perception. This study presents the first theoretical evidence that pinwheel structures function as crucial detectors of spatial contour saliency in the visual cortex. © 2024 Neural information processing systems foundation. All rights reserved.

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An intelligent Resource Scheduling Method with Edge Channel Deployment for BPM 19

An Intelligent Resource Scheduling Method with Edge Channel ...

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2022 IEEE SmartWorld, 19th IEEE International Conference on Ubiquitous Intelligence and computing, 2022 IEEE International Conference on Autonomous and Trusted Vehicles Conference, 22nd IEEE International Conference on Scalable computing and Communications, 2022 IEEE International Conference on Digital Twin, 8th IEEE International Conference on Privacy computing and 2022 IEEE International Conference on Metaverse, SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PriComp/Metaverse 2022

作者： Liu, Bowen Dou, Wanchun Zhou, Xiaokang Zhang, Xuyun Qi, Lianyong Dai, Fei Chen, Chaochao Nanjing University State Key Laboratory for Novel Software Technology Nanjing China Shiga University Faculty of Data Science Hikone Japan Macquarie University Department of Computing Sydney Australia College of Computer and Software Qingdao China Southwest Forestry University College of Big Data and Intelligent Engineering Kunming China Zhejiang University College of Computer Science and Technology Hangzhou China

ISBN: (纸本)9798350346558

Edge computing is a novel computing paradigm that offers kinds of resources at the network edge. In edge computing, terminal users are connected to edge servers via the wireless network and there are various channels in each wireless link. These wireless channels are limited resource while different channel has different cost and service ability. The dynamic changes of users' status make it harder to find an appropriate method to satisfy the BPM requirements of channel deployment. With this observation, it is a tricky challenge to make a trade-off between the system cost(rental price) and the service ability(number of users). In view of this challenge, an intelligent resource scheduling method, named EdgeIRS, is proposed in this paper. In the technical sense, the EdgeIRS method can accommodate most users at the edge with a minimum cost of deploying channel resources in an online way. Its performance is analyzed theoretically and the experiments verify the superiority of the method. © 2022 IEEE.

关键词： Cost effectiveness

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Deformable registration framework for glioma images with absent correspondence based on auxiliary-image-aided intensity-consistency constraint

Deformable registration framework for glioma images with abs...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Tang, Kun Wang, Lihui Yang, Menglong Xu, Jingwen Cheng, Xinyu Zhang, Jian Zhu, Yuemin Wei, Hongjiang Ministry of Education State Key Laboratory of Public Big Data College of Computer Science and Technology Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province Engineering Research Center of Text Computing & Cognitive Intelligence Guiyang China Univ Lyon Insa Lyon Cnrs Inserm Creatis Umr 5220 U1206 Lyon France Shanghai Jiao Tong University School of Biomedical Engineering Shanghai200240 China

ISBN: (纸本)9798350386226

Considering the tumor aggressive nature and the significant changes in anatomical structure, aligning the preoperative and follow up scans of glioma patients remains a challenge due to the presence of regions with absent correspondence. To address this challenge, this work proposed a novel bidirectional unsupervised deformable image registration framework for image pairs with missing correspondence based on an auxiliary-image-aided intensity-consistency constraint (ICC) strategy. Specifically, for any fixed and moving image pairs, we introduced an auxiliary image and warped it directly to fixed/moving image or warped it twice through a transition of moving/fixed image. By comparing the difference between these warped images, the weighting maps to identify and exclude regions with absent correspondence between fixed and moving image pairs can be generated. To verify the effectiveness of the proposed framework, we combined it with several deep learning-based registration models and tested it on BraTS-Reg challenge dataset, the results demonstrated that the proposed ICC strategy can improve the registration performance for all the models, with the improvement of average target registration error (TRE) and success rate (SR) being up to 44.9% and 66.7%, respectively. Comparing against the best existing forward-backward consistency strategy for dealing with missing correspondence registration, our auxiliary-image-aided ICC strategy can also decrease average TRE by 2.9%, demonstrating the superiority of the proposed framework. The present work is not limited to the glioma images, it can be used to address the registration problems for any image pairs with absent correspondence or inconsistent intensity. © 2024 IEEE.

关键词： Image registration

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MULTIPLE HEADS ARE BETTER THAN ONE: MIXTURE OF MODALITY KNOWLEDGE EXPERTS FOR ENTITY REPRESENTATION LEARNING

arXiv

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arXiv 2024年

作者： Zhang, Yichi Chen, Zhuo Guo, Lingbing Xu, Yajing Hu, Binbin Liu, Ziqi Zhang, Wen Chen, Huajun College of Computer Science and Technology Zhejiang University China ZJU-Ant Group Joint Lab of Knowledge Graph China Ant Group China School of Software Technology Zhejiang University China Zhejiang Key Laboratory of Big Data Intelligent Computing China

Learning high-quality multi-modal entity representations is an important goal of multi-modal knowledge graph (MMKG) representation learning, which can enhance reasoning tasks within the MMKGs, such as MMKG completion (MMKGC). The main challenge is to collaboratively model the structural information concealed in massive triples and the multi-modal features of the entities. Existing methods focus on crafting elegant entity-wise multi-modal fusion strategies, yet they overlook the utilization of multi-perspective features concealed within the modalities under diverse relational contexts. To address this issue, we introduce a novel framework with Mixture of Modality Knowledge experts (MOMOK for short) to learn adaptive multi-modal entity representations for better MMKGC. We design relation-guided modality knowledge experts to acquire relation-aware modality embeddings and integrate the predictions from multi-modalities to achieve joint decisions. Additionally, we disentangle the experts by minimizing their mutual information. Experiments on four public MMKG benchmarks demonstrate the outstanding performance of MOMOK under complex scenarios. Our code and data are available at https://***/zjukg/MoMoK. Copyright © 2024, The Authors. All rights reserved.

关键词： Contrastive Learning

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Risk analysis of system security based on evidence theory

Risk analysis of system security based on evidence theory

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2010 International Conference on Computer Design and Applications, ICCDA 2010

作者： Xu, Peida Xu, Jianling Deng, Yong Su, Xiaoyan Key Laboratory of Digital Agricultural Early-warning Technology Ministry of Agriculture of China Beijing China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University China School of Electronics and Information Technology Shanghai Jiao Tong University Shanghai China Grain Economics Institute Nanjing University of Finance and Economics Nanjing China Hangzhou Key Lab. of E-Business and Information Security Hangzhou Normal University Hanzhou Zhejiang China Hangzhou Key Lab. of E-Business and Information Security Hangzhou Normal University Shanghai China

ISBN: (纸本)9781424471638

Risk evaluation is very important to the design and improvement of physical protection systems. In this paper, an evaluation method of multi-source information fusion is proposed based on the D-S evidence theory. In the proposed method, each individual component of the protection system in the simulated plane is modeled. Then, the threat report of each component according to the specific tactics is determined based on its real environment. Finally, the comprehensive threat distribution is obtained based on through the D-S evidence theory to combine multi-sources information. The proposed method can easily applied to the evaluation of the effectiveness of the protection system. We make the total threat of the protection system lowest through changes of the protection resources allocation. A numerical example is used to illustrate the efficiency of the proposed method. © 2010 IEEE.

关键词： Information fusion

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Tokenization, Fusion, and Augmentation: Towards Fine-grained Multi-modal Entity Representation

arXiv

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arXiv 2024年

Multi-modal knowledge graph completion (MMKGC) aims to discover unobserved knowledge from given knowledge graphs, collaboratively leveraging structural information from the triples and multi-modal information of the entities to overcome the inherent incompleteness. Existing MMKGC methods usually extract multi-modal features with pre-trained models, resulting in coarse handling of multi-modal entity information, overlooking the nuanced, fine-grained semantic details and their complex interactions. To tackle this shortfall, we introduce a novel framework MYGO to tokenize, fuse, and augment the fine-grained multi-modal representations of entities and enhance the MMKGC performance. Motivated by the tokenization technology, MYGO tokenizes multi-modal entity information as fine-grained discrete tokens and learns entity representations with a cross-modal entity encoder. To further augment the multi-modal representations, MYGO incorporates fine-grained contrastive learning to highlight the specificity of the entity representations. Experiments on standard MMKGC benchmarks reveal that our method surpasses 19 of the latest models, underlining its superior performance. Code and data can be found in https://***/zjukg/MyGO. Copyright © 2024, The Authors. All rights reserved.

关键词： Knowledge graph

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Detection of Children’s Molars Based on Noise Filter

Research Square

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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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A Study of 10 Rotating Radio Transients Using Parkes Radio Telescope

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Research in Astronomy and Astrophysics 2024年第4期24卷 114-123页

作者： Xinhui Ren Jingbo Wang Wenming Yan Jintao Xie Shuangqiang Wang Yirong Wen Yong Xia Xinjiang Astronomical Observatory Chinese Academy of SciencesUrumqi 830011China University of Chinese Academy of Sciences Beijing 100049China Institute of Optoelectronic Technology Lishui UniversityLishui 323000China Xinjiang Key Laboratory of Radio Astrophysics Urumqi 830011China Research Center for Intelligent Computing Platforms Zhejiang LaboratoryHangzhou 311100China

Rotating Radio Transients(RRATs)are a relatively new subclass of pulsars that emit detectable radio bursts *** analyzed 10 RRATs observed using the Parkes telescope,with eight of these observed via the ultra-wide-bandwidth low-frequency(UWL)*** measured the burst rate and produced integrated profiles spanning multiple frequency bands for three *** also conducted a spectral analysis on both integrated pulses and individual pulses of three *** of their integrated pulses follow a simple power law,consistent with the known range of pulsar spectral *** average spectral indices of single pulses are-0.9,-1.2,and-1.0 respectively,which are within the known range of pulsar spectral ***,we find that the spreads of single-pulse spectral indices for these RRATs(ranging from-3.5 to+0.5)are narrower compared to what has been observed in other ***,the average spectral index and scatter of single pulses are both relatively *** the remaining five RRATs observed at the UWL receiver,we also provide the upper limits on fluence and flux *** addition,we obtain the timing solution of PSR *** analysis shows that PSRs J1919+1745,J1709-43,and J1649-4653 are potentially nulling pulsars or weak pulsars with sparse strong pulses.

关键词： (stars:)pulsars:general stars:neutron stars:individual(PSRs J1919+1745.1909+0641,0628+0909)

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Mutual Information Maximization for Effective Lip Reading

Mutual Information Maximization for Effective Lip Reading

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International Conference on Automatic Face and Gesture Recognition

作者： Xing Zhao Shuang Yang Shiguang Shan Xilin Chen Zhejiang University of Technology Hangzhou China Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS Beijing China University of Chinese Academy of Sciences Beijing China

ISBN: (数字)9781728130798

ISBN: (纸本)9781728130804

Lip reading has received an increasing research interest in recent years due to the rapid development of deep learning and its widespread potential applications. One key point to obtain good performance for the lip reading task depends heavily on how effective the representation can be used to capture the lip movement information and meanwhile to resist the noises resulted by the change of pose, lighting conditions, speaker's appearance, speaking speed and so on. Towards this target, we propose to introduce the mutual information constraints on both the local feature's level and the global sequence's level to enhance the relations of them with the speech content. On the one hand, we require the features generated at each time step to carry a strong relation with the speech content by imposing the local mutual information maximization constraint (LMIM), so as to improve the model's ability to discover fine-grained lip movements and the finegrained differences between words with similar pronunciation, such as “spend” and “spending”. On the other hand, we introduce the mutual information maximization constraint on the global sequence's level (GMIM), to make the model be able to pay more attention to discriminate key frames related with the speech content, and less to various noises appeared in the speaking process. By combining these two advantages together, the proposed method is expected to be both discriminative and robust for effective lip reading. To verify this method, we evaluate on two large-scale benchmarks whose videos are collected from several TV shows with a wide coverage of the speaking conditions. We perform a detailed analysis and comparison on several aspects, including the comparison with the baseline of the LMIM and GMIM, and the visualization of the learned representation. The results not only prove the effectiveness of the proposed method but also report new state-of-the-art performance on both the two benchmarks.

关键词： Lips Hidden Markov models Mutual information Task analysis Visualization Feature extraction Deep learning

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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

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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