检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Yao, Zhi Tang, Zhiqing Lou, Jiong Shen, Ping Jia, Weijia Institute of Artificial Intelligence and Future Networks Beijing Normal University Zhuhai519087 China School of Artificial Intelligence Beijing Normal University Beijing100875 China Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai200240 China Guangdong Key Lab of AI and Multi-Modal Data Processing BNU-HKBU United International College Zhuhai519087 China

The Large Language Model (LLM) has gained significant popularity and is extensively utilized across various domains. Most LLM deployments occur within cloud data centers, where they encounter substantial response delays and incur high costs, thereby impacting the Quality of Services (QoS) at the network edge. Leveraging vector database caching to store LLM request results at the edge can substantially mitigate response delays and cost associated with similar requests, which has been overlooked by previous research. Addressing these gaps, this paper introduces a novel Vector database-assisted cloud-Edge collaborative LLM QoS Optimization (VELO) framework. Firstly, we propose the VELO framework, which ingeniously employs vector database to cache the results of some LLM requests at the edge to reduce the response time of subsequent similar requests. Diverging from direct optimization of the LLM, our VELO framework does not necessitate altering the internal structure of LLM and is broadly applicable to diverse LLMs. Subsequently, building upon the VELO framework, we formulate the QoS optimization problem as a Markov Decision Process (MDP) and devise an algorithm grounded in Multi-Agent Reinforcement Learning (MARL) to decide whether to request the LLM in the cloud or directly return the results from the vector database at the edge. Moreover, to enhance request feature extraction and expedite training, we refine the policy network of MARL and integrate expert demonstrations. Finally, we implement the proposed algorithm within a real edge system. Experimental findings confirm that our VELO framework substantially enhances user satisfaction by concurrently diminishing delay and resource consumption for edge users utilizing LLMs. Copyright © 2024, The Authors. All rights reserved.

关键词： Vectors

来源：评论

学校读者我要写书评

暂无评论

CoBe - Coded Beacons for Localization, Object Tracking, and SLAM Augmentation

CoBe - Coded Beacons for Localization, Object Tracking, and ...

引用

IEEE International Conference on Automation science and Engineering (CASE)

作者： Roman Rabinovich Ibrahim Jubran Aaron Wetzler Ron Kimmel Geometric Image Processing (GIP) Lab Computer Science Department Technion - Israel Institute of Technology Israel Robotics & Big Data (RBD) Lab Computer Science Department University of Haifa Israel

ISBN: (数字)9781728169040

ISBN: (纸本)9781728169057

This paper presents a novel beacon light coding protocol, which enables fast and accurate identification of the beacons in an image. The protocol is provably robust to a predefined set of detection and decoding errors and does not require any synchronization between the beacons themselves and the optical sensor. A detailed guide is then given for developing an optical tracking and localization system, which is based on the suggested protocol and readily available hardware. Such a system operates either as a standalone system for recovering the six degrees of freedom of fast moving objects, or integrated with existing SLAM pipelines providing them with error-free and easily identifiable landmarks. Based on this guide, we implemented a low-cost positional tracking system which can run in real-time on an IoT board. We evaluate our system's accuracy and compare it to other popular methods which utilize the same optical hardware, in experiments where the ground truth is known. A companion video containing multiple real-world experiments demonstrates the accuracy, speed, and applicability of the proposed system in a wide range of environments and real-world tasks. Open source code is provided to encourage further development of low-cost localization systems integrating the suggested technology at its navigation core.

关键词： Optical sensors Robustness Simultaneous localization and mapping Protocols Decoding Adaptive optics Optical imaging

来源：评论

学校读者我要写书评

暂无评论

Learning from partially labeled data 28

Learning from partially labeled data

引用

28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2020

作者： Mehrkanoon, Siamak Huang, Xiaolin Suykens, Johan A.K. Department of Data Science and Knowledge Engineering Maastricht University Netherlands Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China Department of Electrical Engineering ESAT-STADIUS KU Leuven LeuvenB-3001 Belgium

ISBN: (纸本)9782875870742

Providing sufficient labeled training data in many application domains is a laborious and costly task. Designing models that can learn from partially labeled data, or leveraging labeled data in one domain and unlabeled data in a different but related domain is of great interest in many applications. In particular, in this context one can refer to semi-supervised modelling, transfer learning, domain adaptation and multi-view learning among oth- ers. There are several possibilities for designing such models ranging from shallow to deep models. These type of models have received increasing in- terest due to their successful applications in real-life problems. This paper provides a brief overview of recent techniques in learning from partially labeled data. © ESANN 2020 - Proceedings, 28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning.

关键词： Neural networks

来源：评论

学校读者我要写书评

暂无评论

Expected and unexpected routes to synchronization in a system of swarmalators

引用

Physical Review E 2024年第6期110卷 L062301-L062301页

作者： Steve J. Kongni Thierry Njougouo Patrick Louodop Robert Tchitnga Fernando F. Ferreira Hilda A. Cerdeira Research Unit Condensed Matter Electronics and Signal Processing University of Dschang P.O. Box 67 Dschang Cameroon Dschang Cameroon IMT School for Advanced Studies 55100 Lucca Italy Faculty of Computer Science and Namur Institute for Complex Systems (naXys) University of Namur 5000 Namur Belgium Department of Electrical and Electronic Engineering Faculty of Engineering and Technology (FET) University of Buea Buea Cameroon ICTP South American Institute for Fundamental Research São Paulo State University (UNESP) Instituto de Física Teórica Rua Doutor Bento Teobaldo Ferraz 271 Bloco II Barra Funda 01140-070 São Paulo Brazil Department of Physics-FFCLRP University of São Paulo Ribeirao Preto 14040-901 São Paulo Brazil São Paulo State University (UNESP) Instituto de Física Teórica Rua Doutor Bento Teobaldo Ferraz 271 Bloco II Barra Funda 01140-070 São Paulo Brazil Epistemic Gomez & Gomez Ltda. Micro Empresa (ME) Rua Paulo Franco 520 Vila Leopoldina 05305-031 São Paulo Brazil

Systems of oscillators whose internal phases and spatial dynamics are coupled, swarmalators, present diverse collective behaviors which in some cases lead to explosive synchronization in a finite population as a function of the coupling parameter between internal phases. Near the synchronization transition, the phase energy of the particles is represented by the XY model, and they undergo a transition which can be of the first order or the second depending on the distribution of natural frequencies of their internal dynamics. The first-order transition is obtained after an intermediate state (static wings phase wave state) from which the nodes, in cascade over time, achieve complete phase synchronization at a precise value of the coupling constant. For a particular case of natural frequencies distribution, a new phenomenon, the rotational splintered phase wave state, is observed and leads progressively to synchronization through clusters switching alternatively from one to two and for which the frequency decreases as the phase coupling increases.

关键词： Collective behavior in networks Dynamics of networks Network phase transitions Synchronization transition

来源：评论

学校读者我要写书评

暂无评论

Blip-Up Blip-Down Circular EPI (BUDA-cEPI) for Distortion-Free dMRI with Rapid Unrolled Deep Learning Reconstruction

arXiv

引用

arXiv 2023年

作者： Yarach, Uten Chatnuntawech, Itthi Liao, Congyu Teerapittayanon, Surat Iyer, Siddharth Srinivasan Kim, Tae Hyung Haldar, Justin Cho, Jaejin Bilgic, Berkin Hu, Yuxin Hargreaves, Brian Setsompop, Kawin Radiologic Technology Department Associated Medical Sciences Chiang Mai University Chiang Mai Thailand National Nanotechnology Center National Science and Technology Development Agency Pathum Thani Thailand Department of Radiology Stanford University StanfordCA United States Department of Electrical Engineering Stanford University StanfordCA United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States Department of Computer Engineering Hongik University Seoul Korea Republic of Signal and Image Processing Institute Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los AngelesCA United States Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital CharlestownMA United States Department of Radiology Harvard Medical School BostonMA United States Department of Bioengineering Stanford University StanfordCA United States Packard Electrical Engineering Building 350 Jane Stanford Way StanfordCA94305 United States

Purpose: We implemented the blip-up, blip-down circular echo planar imaging (BUDA-cEPI) sequence with readout and phase partial Fourier to reduced off-resonance effect and T2* blurring. BUDA-cEPI reconstruction with S-based low-rank modeling of local k-space neighborhoods (S-LORAKS) is shown to be effective at reconstructing the highly under-sampled BUDA-cEPI data, but it is computationally intensive. Thus, we developed an ML-based reconstruction technique termed "BUDA-cEPI RUN-UP" to enable fast reconstruction. Methods: BUDA-cEPI RUN-UP – a model-based framework that incorporates off-resonance and eddy current effects was unrolled through an artificial neural network with only six gradient updates. The unrolled network alternates between data consistency (i.e., forward BUDA-cEPI and its adjoint) and regularization steps where U-Net plays a role as the regularizer. To handle the partial Fourier effect, the virtual coil concept was also incorporated into the reconstruction to effectively take advantage of the smooth phase prior, and trained to predict the ground-truth images obtained by BUDA-cEPI with S-LORAKS. Results: BUDA-cEPI with S-LORAKS reconstruction enabled the management of off-resonance, partial Fourier, and residual aliasing artifacts. However, the reconstruction time is approximately 225 seconds per slice, which may not be practical in a clinical setting. In contrast, the proposed BUDA-cEPI RUN-UP yielded similar results to BUDA-cEPI with S-LORAKS, with less than a 5% normalized root mean square error detected, while the reconstruction time is approximately 3 seconds. Conclusion: BUDA-cEPI RUN-UP was shown to reduce the reconstruction time by ~88x when compared to the state-of-the-art technique, while preserving imaging details as demonstrated through DTI application. © 2023, CC BY.

关键词： Magnetic resonance imaging

来源：评论

学校读者我要写书评

暂无评论

An Interpretable Galaxy Morphology Classification Approach Using Modified Squeeze Net and Local Interpretable Model-agnostic Explanation

引用

Research in Astronomy and Astrophysics 2025年第6期25卷 220-239页

作者： Kam Meng Goh Derrick Hiang Yaol Lim Zhen Dong Sham Kolla Bhanu Prakash Centre for Multimodal Signal Processing Faculty of Engineering and Technology Tunku Abdul Rahman University of Management and Technology Starlight Education Group Faculty of Institute for Advanced Studies UM Power Energy Dedicated Advanced Centre Universiti Malaya Department of Computer Science & Engineering DST—FIST Sponsored DepartmentKoneru Lakshmaiah Education Foundation

The recent surge in computer vision and deep learning has attracted significant attention within the galaxy morphology community. Various models have been implemented for galaxy morphology prediction with nearperfect accuracy for certain classes. However, many studies treat deep learning models as black-box entities,lacking interpretability of their predictions. To address these limitations while ensuring good performance, we introduced an Improved Squeeze Net(I-Squeeze Net) by incorporating unique residual connections to improve the prediction performance, and we utilize Local Interpretable Model-Agnostic Explanations(LIME) to understand the interpretability. We evaluated the simplified Squeeze Net and I-Squeeze Net, with both channel and vertical concatenation, and compared their performances with those of some exiting methods such as Dieleman's CNN,VGG13, Dense Net121, Res Net50, Res Next50, Res Next101, DSCNN and customized CNN in classifying galaxy objects using a dataset from the publicly available Galaxy Zoo Data Challenge Project. Our experiments showed that I-Squeeze Net with vertical concatenation achieved the highest average accuracy of 94.08% compared to other methods. Beyond achieving high accuracy, the application of LIME for model interpretation sheds light on the machine learning features and reasoning processes behind the model's predictions. This information provides valuable insight into the galaxy morphology decision-making process, paving the way for further functional enhancements.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Five A+Network: You Only Need 9K Parameters for Underwater image Enhancement

arXiv

引用

arXiv 2023年

作者： Jiang, Jingxia Ye, Tian Bai, Jinbin Chen, Sixiang Chai, Wenhao Jun, Shi Liu, Yun Chen, Erkang School of Ocean Information Engineering Jimei University Xiamen China Department of Computer Science National University of Singapore Singapore ZJU-UIUC Institute Zhejiang University Hanzhou China The School of Information Science and Engineering Xinjiang University Uruqmi China College of Artificial Intelligence Southwest University Chongqing China Fujian Provincial Key Laboratory of Oceanic Information Perception and Intelligent Processing China

A lightweight underwater image enhancement network is of great significance for resource-constrained platforms, but balancing model size, computational efficiency, and enhancement performance has proven difficult for previous approaches. In this work, we propose the Five A+Network (FA+Net), a highly efficient and lightweight real-time underwater image enhancement network with only ∼ 9k parameters and ∼ 0.01s processing time. The FA+Net employs a two-stage enhancement structure. The strong prior stage aims to decompose challenging underwater degradations into sub-problems, while the fine-grained stage incorporates multi-branch color enhancement module and pixel attention module to amplify the network's perception of details. To the best of our knowledge, FA+Net is the only network with the capability of real-time enhancement of 1080P images. Thorough extensive experiments and comprehensive visual comparison, we show that FA+Net outperforms previous approaches by obtaining state-of-the-art performance on multiple datasets while significantly reducing both parameter count and computational complexity. The code is open source at https://***/Owen718/FiveAPlusNetwork. Copyright © 2023, The Authors. All rights reserved.

关键词： Computational efficiency

来源：评论

学校读者我要写书评

暂无评论

Combined impact of grey and superficial white matter abnormalities: implications for epilepsy surgery

arXiv

引用

arXiv 2025年

作者： Kozma, Csaba Horsley, Jonathan Hall, Gerard Simpson, Callum de Tisi, Jane Miserocchi, Anna McEvoy, Andrew W. Vos, Sjoerd B. Winston, Gavin P. Wang, Yujiang Duncan, John S. Taylor, Peter N. School of Computing Newcastle University Newcastle upon Tyne United Kingdom Translational and Clinical Research Institute Faculty of Medical Sciences Newcastle University Newcastle upon Tyne United Kingdom Department of Clinical and Experimental Epilepsy UCL Queen Square Institute of Neurology University College London London United Kingdom Western Australia National Imaging Facility The University of Western Australia Nedlands Australia Centre for Medical Image Computing Computer Science Department University College London London United Kingdom Department of Medicine Queen’s University KingstonON Canada

Drug-resistant focal epilepsy is associated with abnormalities in the brain in both grey matter (GM) and superficial white matter (SWM). However, it is unknown if both types of abnormalities are important in supporting seizures. Here, we test if surgical removal of GM and/or SWM abnormalities relates to post-surgical seizure outcome in people with temporal lobe epilepsy (TLE). We analyzed structural imaging data from 143 TLE patients (pre-op dMRI and pre-op T1-weighted MRI) and 97 healthy controls. We calculated GM volume abnormalities and SWM mean diffusivity abnormalities and evaluated if their surgical removal distinguished seizure outcome groups post-surgically. At a group level, GM and SWM abnormalities were most common in the ipsilateral temporal lobe and hippocampus in people with TLE. Analyzing both modalities together, compared to in isolation, improved surgical outcome discrimination (GM AUC = 0.68, p 1,2 outcomes. These findings suggest that regions identified as abnormal from both diffusion-weighted and T1-weighted MRIs are involved in the epileptogenic network and that resection of both types of abnormalities may enhance the chances of living without disabling seizures. Copyright © 2025, The Authors. All rights reserved.

关键词： Transplantation (surgical)

来源：评论

学校读者我要写书评

暂无评论

Beam Scanning for Integrated Sensing and Communication in IRS-aided mmWave Systems

Beam Scanning for Integrated Sensing and Communication in IR...

引用

IEEE Workshop on Signal processing Advances in Wireless Communications (SPAWC)

作者： Renwang Li Xiaodan Shao Shu Sun Meixia Tao Rui Zhang Department of Electronic Engineering Shanghai Jiao Tong University Shanghai China Shanghai Key Laboratory of Digital Media Processing and Transmission Shanghai Jiao Tong University Shanghai China School of Science and Engineering Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen China Department of Electrical and Computer Engineering National University of Singapore Singapore

This paper investigates an intelligent reflecting surface (IRS) aided millimeter-wave integrated sensing and communication (ISAC) system. Specifically, based on the passive beam scanning in the downlink, the IRS finds the optimal beam for reflecting the signals from the base station to a communication user. Meanwhile, the IRS estimates the angle of a nearby target based on its echo signal received by the sensing elements mounted on the IRS (i.e., semi-passive IRS). We propose an ISAC protocol for achieving the above objective via simultaneous (beam) training and sensing (STAS). Then, we derive the achievable rate of the communication user and the Cramer-Rao bound (CRB) of the angle estimation for the sensing target in closed-form. The achievable rate and CRB exhibit different performance against the duration of beam scanning. Specifically, the average achievable rate initially rises and subsequently declines, while the CRB monotonically decreases. Consequently, the duration of beam scanning should be carefully selected to balance communication and sensing performance. Simulation results have verified our analytical findings and shown that, thanks to the efficient use of downlink beam scanning signal for simultaneous communication and target sensing, the STAS protocol outperforms the benchmark protocol with orthogonal beam training and sensing.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Real-Time Data Collection of Wsn Based on Trajectory Optimization of Laser-Charged Uav

SSRN

引用

SSRN 2023年

作者： Luo, Chuanwen Hong, Yi Hou, Yunan Zhu, Yuqing Li, Deying Yu, Dongxiao Wu, Weili School of Information Science and Technology Beijing Forestry University Beijing100083 China Engineering Research Center for Forestry-oriented Intelligent Information Processing of National Forestry and Grassland Administration Beijing100083 China Research Center of Applied Mathematics and Machine Intelligence Zhejiang Lab Zhejiang Hangzhou311121 China Department of Computer Science California State University Los AngelesCA90032 United States School of Information Renmin University of China Beijing100872 China School of Computer Science and Technology Institute of Intelligent Computing Shandong University Qingdao266510 China Department of Computer Science The University of Texas at Dallas RichardsonTX75080 United States

Unmanned Aerial Vehicle (UAV) can be used as wireless aerial mobile base station for collecting data from sensors in UAV-based Wireless Sensor Networks (WSNs), which is crucial for providing seamless services and improving the performance in the next generation wireless networks. However, since the UAV are powered by batteries with limited energy capacity, the UAV can not complete data collection tasks of all sensors without energy replenishment when a large number of sensors are deployed over large monitoring areas. To overcome this problem, this paper study the Real-time Data Collection with Laser-charging UAV (RDCL) problem, where the UAV is used to collect data from a given WSN and replenished energy by Laser Beam Directors (LBDs). The problem aims at optimizing the flight trajectory of UAV for ensuring the real-time performance of data, which is to design the detailed hovering and traveling plans of UAV for collecting data from sensors and charged by LBDs such that all sensory data of WSN are collected by UAV and transported to the base *** prove that the RDCL problem is NP-hard. To solve the problem, we first study two sub-problems, the Trajectory Optimization of UAV for Data Collection (TODC) problem and the Charging Trajectory Optimization of UAV (CTO) problem, whose objectives are to find the optimal flight plans of UAV in the data collection areas and charging areas, respectively. Then we propose an approximation algorithm to solve each of them with the constant factor. Afterwards, we propose an approximation algorithm to solve the RDCL problem based on TODC and CTO problems. Finally, the proposed algorithm is verified by extensive simulations. © 2023, The Authors. All rights reserved.

关键词： Wireless sensor networks

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：