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A dynamic point cloud fast compression framework based on eliminating spatial and temporal redundancy

Multimedia Tools and Applications 2025年 1-19页

作者： Su, Kainan Wang, Zunran Yang, Chenguang The Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and Engineering South China University of Technology Guangzhou510641 China Huawei Technologies Co Ltd Shenzhen518028 China

Dynamic point clouds can be compressed by eliminating spatial and temporal redundancy, but few research studies have considered both simultaneously. Existing research can only distinguish the specific foreground and background of the scene, achieving the former with a limited compression ratio, while the latter relies on 3D motion estimation with high computing complexity. Therefore, it is difficult to meet the real-time requirement of building remote human-robot interaction system. Aiming at the shortcomings of the above methods, a dynamic point cloud fast compression framework based on eliminating spatial and temporal redundancy is proposed. On the one hand, for eliminating the spatial redundancy, the information of the recognized objects in point cloud data will be replaced with their categories and poses. On the other hand, we eliminate the temporal redundancy by using the motion vector of the point cloud macroblock. Specifically, in order to reduce cost time of the 3D motion estimation, we firstly introduce the 2D image ORB feature to calculate the motion vector from current frame to key frame, and then look for the similar macroblock in key frame. Thus, the information of the macroblocks similar to the key frame in the current frame is replaced by the index of the corresponding macroblocks of the key frame and the motion vector. Experimental results show that the proposed method has higher computational efficiency and compression quality than the existing compression algorithm. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Semantic Segmentation

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Optimizing Clustering Approaches in Cloud Environments

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2023年第19期17卷 70-94页

作者： Al-Ghuwairi, Abdel-Rahman Al-Fraihat, Dimah Sharrab, Yousef Kreishan, Yazeed Alsarhan, Ayoub Idhaim, Hasan Qahmash, Ayman Department of Software Engineering Faculty of Prince Al-Hussein Bin Abdallah II for Information Technology The Hashemite University Zarqa Jordan Department of Software Engineering Faculty of Information Technology Isra University Amman Jordan Department of Data Science and Artificial Intelligence Faculty of Information Technology Isra University Amman Jordan Department of Information Technology Faculty of Prince Al-Hussein Bin Abdallah II for Information Technology The Hashemite University Zarqa Jordan Department of Information Systems Faculty of Prince Al-Hussein Bin Abdallah II for Information Technology The Hashemite University Zarqa Jordan Department of Information Systems Computer Science College King Khalid University Abha Saudi Arabia

This study focuses on the challenge of developing abstract models to differentiate various cloud resources. It explores the advancements in cloud products that offer specialized services to meet specific external needs. The study proposes a new approach to request processing in clusters, improving downtime, load distribution, and overall performance. A comparison of three clustering approaches is conducted: local single cluster, local multiple clusters, and multiple cloud clusters. Performance, scalability, fault tolerance, resource allocation, availability, and cost-effectiveness are evaluated through experiments with 50 requests. All three approaches achieve a 100% success rate, but processing times vary. The local single cluster has the longest duration, while the local multiple clusters and multiple cloud clusters perform better and offer faster processing, scalability, fault tolerance, and availability. From a cost perspective, the local single cluster and local multiple clusters incur capital and operational expenses, while the multiple cloud clusters follow a pay-as-you-go model. Overall, the local multiple clusters and multiple cloud clusters outperform the local single cluster in terms of performance, scalability, fault tolerance, resource allocation, availability, and cost-effectiveness. These findings provide valuable insights for selecting appropriate clustering strategies in cloud environments. © 2023 by the authors of this article. Published under CC-BY.

关键词： Fault tolerance

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Delayed Self-heterodyne Interferometry Enabling 4.8 Tb/s Coherent Transmission and Simultaneous Vibration Sensing with 100 kHz Linewidth ECLs

Delayed Self-heterodyne Interferometry Enabling 4.8 Tb/s Coh...

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2024 Asia Communications and Photonics Conference, ACP 2024 and International Conference on information Photonics and Optical Communications, IPOC 2024

作者： Hao, Yaguang Xiang, Qian Yang, Yanfu Yue, Bing Fan, Linsheng Hu, Weisheng Xu, Yifan Li, Jiali Li, Xueyang Departmet of Circuits and Systems Pengcheng Laboratory Shenzhen China School of Electronics and Information Engineering Harbin Institute of Technology Shenzhen China

ISBN: (纸本)9798350379266

We relax the laser linewidth requirement for carrier phase-detection based vibration sensing via the delayed self-heterodyne interferometry scheme. In addition, we transmit net 4.8 Tb/s/λ signals over 55.9 km of weakly coupled seven-core fiber with joint vibration sensing utilizing 100 kHz linewidth external cavity lasers. © 2024 IEEE.

关键词： Linewidth

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Improving the Efficiency of Smart Grid Scheduling: A Linear Regression Model with Meta Job information 2

Improving the Efficiency of Smart Grid Scheduling: A Linear ...

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2nd International Conference on Cyber Resilience, ICCR 2024

作者： Al-Najjar, Hazem Al-Rousan, Nadia College Of Information Technology University Of Petra Department Of Computer Science Amman Jordan German Jordianian University Faculty Of Electrical Engineering And Information Systems Department Of Computer Engineering Jordan

ISBN: (纸本)9798350394962

In order to forecast the run time of the jobs that were submitted, this research provides two linear regression prediction models that include continuous and categorical factors. A continuous predictor is built using the number of CPUs, average CPU speed, and memory size, whereas a categorical predictor is built using the user ID, group ID, and executable ID. According to the findings, the prediction rates for categorical and continuous predictors are 61% and 1%, respectively. sixty times better than the earlier models, which used continuous variables as a foundational model to determine task complexity and weight. The effectiveness of the categorical predictor in enhancing a job scheduling problem is then evaluated by combining it with three suggested job scheduling strategies. The suggested algorithms incorporated metrics - predicted run time, waiting time, and resource requirement - to select the smallest jobs. According to the results, Algorithm 3 performs better than earlier models in both performance metrics. The variation in total execution time and average waiting time is 1.14 to 1.76 and 4.5, respectively compared to previous models, Additionally, Algorithms 1 and 2 demonstrating superior performance in every scenario. © 2024 IEEE.

关键词： Grid computing

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Universality class of machine learning for critical phenomena

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science China(Physics,Mechanics & Astronomy) 2023年第12期66卷 63-70页

作者： Gaoke Hu Yu Sun Teng Liu Yongwen Zhang Maoxin Liu Jingfang Fan Wei Chen Xiaosong Chen School of Systems Science and Institute of Nonequilibrium Systems Beijing Normal UniversityBeijing 100875China Data Science Research Center Faculty of ScienceKunming University of Science and TechnologyKunming 650500China State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China

Herein,percolation phase transitions on a two-dimensional lattice were studied using machine learning *** reveal that different phase transitions belonging to the same universality class can be identified using the same neural networks(NNs),whereas phase transitions of different universality classes require different *** on this finding,we proposed the universality class of machine learning for critical ***,we investigated and discussed the NNs of different universality *** research contributes to machine learning by relating the NNs with the universality class.

关键词： universality class machine learning percolation

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Driving deep-learning-based metasurface design with Kramers-Kronig relations

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Physical Review Applied 2024年第4期22卷 L041002页

作者： Guangfeng You Chao Qian Shurun Tan Erping Li Hongsheng Chen ZJU-UIUC Institute Interdisciplinary Center for Quantum Information State Key Laboratory of Extreme Photonics and Instrumentation ZJU-Hangzhou Global Science and Technology Innovation Center Key Laboratory of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang Jinhua Institute of Zhejiang University

Two-decade strides in metasurfaces have enabled a multitude of theoretical breakthroughs and experimental discoveries that outride established comprehension. Deep learning has recently found favor for expediting metasurface design and unearthing complex light-matter interactions, in contrast to resource-intensive numerical simulations. However, most “black box” algorithms lack enough discernment on parsing internal physical connections. Here, we propose a physical adversary channel to be complementary to gradient descent channel by embedding the Kramers-Kronig (KK) relations into a neural network, quantifying the inherent spectral contradictions at the output side. We evaluate the superiority of the KK-driven neural network in forward prediction and inverse metasurface design by modifying loss function and shaping probability distribution in latent space, respectively. The exceptional outcome suggests that the similarity between output and given spectra reaches up to 99.8% and maintains an extremely high fidelity even in a mutant band. Our work provides a physically explicable perspective to explain “black box” models, possibly reviving intelligent metasurface applications.

关键词： Inverse problems Artificial neural networks Metamaterials Metasurfaces Deep learning Electromagnetic wave theory

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Adaptive Filtering for UAV Integrated Navigation Based on Noise Variance

Adaptive Filtering for UAV Integrated Navigation Based on No...

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2023 China Automation Congress, CAC 2023

作者： Zhu, Jialu Zhao, Zhongyuan Ge, Quanbo Luo, Zijuan College of Automation Nanjing University of Information Science and Technology Nanjing China Technology GroupCorporation Key Laboratory of Information Systems Engineering The 28th Research Institute of ChinaElectronics Nanjing China

ISBN: (纸本)9798350303759

The Kalman filter is often used as the data fusion algorithm in the GPS/SINS integrated navigation system of the UAV. However, in practical applications, the traditional Kalman filter lacks the ability to deal with the statistical characteristics of noise, which are difficult to obtain and vary with the environment. Therefore, this paper first designs a noise estimator based on reliability for the problem that it is difficult to obtain the statistical characteristics of noise in practical applications;secondly, the measurement noise is updated separately after the Kalman measurement update to reduce the noise caused by noise changes. Finally, the simulation experiment verifies that the adaptive filter designed in this paper can achieve better data fusion in the application of UAV GPS/SINS integrated navigation, and has higher robustness and fault tolerance. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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DDCTrack： Dynamic Token Sampling for Efficient UAV Transformer Tracking 27th

DDCTrack： Dynamic Token Sampling for Efficient UAV Transfor...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Du, Guocai Zhou, Peiyong Yadikar, Nurbiya Aysa, Alimjan Ubul, Kurban College of Information Science and Engineering Xinjiang University Urumqi830046 China The Key Laboratory of Multilingual Information Technology Xinjiang University Urumqi830046 China

ISBN: (纸本)9783031783531

Although state-of-the-art transformer models have shown promising results in unmanned aerial vehicle (UAV) tracking, they come with high computational demands. Existing tracking methods aim to reduce computational complexity by controlling the number of tokens. However, this method is not effective for all tracking methods. Therefore, we propose a novel dynamic token sampling for an efficient UAV transformer tracking framework. Unlike previous transformer-based tracking methods, our method avoids the need for complex head networks like classification and regression. It solely employs our newly designed encoder, comprising three key components: Dynamic Position Embedding, Dynamic Token Sampler, and Convolutional Feed-Forward Network. This module enhances visual representation by scoring and dynamically sampling tokens, allowing for a flexible token count that adapts to target changes within each frame. We utilize a simple image-sequence contrastive loss as the loss function. Our approach not only simplifies the tracking framework, but also achieves state-of-the-art performance on multiple challenging datasets at real-time run speeds. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Aircraft detection

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Unraveling abnormal buried interface anion defect passivation mechanisms depending on cation-induced steric hindrance for efficient and stable perovskite solar cells

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Journal of Energy Chemistry 2023年第5期80卷 1-9,I0001页

作者： Dongmei He Ru Li Baibai Liu Qian Zhou Hua Yang Xuemeng Yu Shaokuan Gong Xihan Chen Baomin Xu Shangfeng Yang Jiangzhao Chen Key Laboratory of Optoelectronic Technology&Systems(Ministry of Education) College of Optoelectronic EngineeringChongqing UniversityChongqing 400044China Institute of High Energy Physics Chinese Academy of Sciences(CAS)Bejing 100049Chin SUSTech Energy Institute for Carbon Neutrality Department of Mechanical and Energy EngineeringSouthern University of Science and TechnologyShenzhen 518055GuangdongChin Department of Materials Science and Engineering Southern University of Science and TechnologyShenzhen 518055GuangdongChina CAS Key Laboratory of Materials for Energy Conversion Department of Materials Science and EngineeringUniversity of Science and Technology of ChinaHefei 230026AnhuiChina

Although ionic liquids(ILs)have been widely employed to heal the defects in perovskite solar cells(PSCs),the corresponding defect passivation mechanisms are not thoroughly understood up to ***,we first reveal an abnormal buried interface anion defect passivation mechanism depending on cationinduced steric *** IL molecules containing the same anion([BF4]^(-))and different sizes of imidazolium cations induced by substituent size are used to manipulate buried *** was revealed what passivated interfacial defects is mainly anions instead of *** and experimental results demonstrate that the large-sized cations can weaken the ionic bond strength between anions and cations,and facilitate the interaction between anions and SnO2as well as perovskites,which is conducive to interfacial defect passivation and ameliorating interfacial *** can be concluded that interfacial chemical interaction strength and defect passivation effect are positively correlated with the size of *** discovery breaks conventional thinking that large-sized modification molecules would weaken their chemical interaction with *** with the control device(21.54%),the device based on 1,3-Bis(1-adamantyl)-imidazolium tetrafluoroborate(BAIMBF4)with maximum size cations achieves a significantly enhanced efficiency of 23.61%along with much increased moisture,thermal and light stabilities.

关键词： Perovskite solar cells Buried interface Ionic liquid Anion defect passivation mechanism Cation-induced steric hindrance

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CNN Model Compression by Merit-Based Distillation 19

CNN Model Compression by Merit-Based Distillation

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19th IEEE International Colloquium on Signal Processing and Its Applications, CSPA 2023

作者： Morikawa, Takumi Kameyama, Keisuke University of Tsukuba Degree Programs in Systems and Information Engineering Graduate School of Science and Technology Tsukuba Japan University of Tsukuba Faculty of Engineering Information and Systems Tsukuba Japan

ISBN: (纸本)9781665476928

Deep learning has advanced dramatically in recent years, and especially large convolutional neural networks (CNNs) have shown outstanding performance in a wide variety of tasks. However, such large-scale CNNs may not be able to be utilized in practice because they require a lot of computational resources. Therefore, there is a need to realize a CNN in a small model that has high performance similar to the large CNN. One method to solve these problems is Distillation, which uses a model of large scale and high performance as the teacher and a small model as the student model, and performs model compression by transferring the knowledge of the teacher model to the student model. However, in distillation, even when the teacher model incorrectly guesses the training input, the student model learns to mimic the teacher. This can prevent the student model from learning better. In this paper, we propose Meritbased Distillation, in which the accuracy of the teacher model's output determines the degree to which the student model mimics the teacher model's output, thereby preventing the student to learn undesired mappings. In the experiment, the effect of the Merit-based Distillation is evaluated. Consequently, the proposed method outperforms the improvements in the generalization by the student models trained by other known methods. © 2023 IEEE.

关键词： Image classification

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