检索结果-内蒙古大学图书馆

Electrical Machines and Drives (ICEMD), International Conference on

作者： Mohammad Afrank Alireza Eikani Ehsan Farmahini Farahani Mojtaba Mirsalim Department of Electrical Engineering Amirkabir University of Technology Tehran Iran Advanced Motion Systems Research Lab School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Electrical Power Research Group School of Engineering Newcastle University Newcastle upon Tyne U.K

This paper executes a comparative analysis between alternative-pole flux-switching and inter-modular biased-flux permanent magnet (PM) motors. Despite their close structural similarities, the former puts magnets not only between stator modules, but also close to the armature windings. However, the inter-modular PM (IMPM) motor only occupies spaces between stator modules. This type of occupation allows this structure to provide a safe operation point for PMs. Not considering the PM’s recoil-phenomenon, the torque density of the IMPM motor is not as significant as the alternative-pole flux-switching PM (AP-FSPM) motor. This is because of the four-operating mode of the AP-FSPM structure which enables it to increase the torque density by utilizing the PMs in every moment of the operation. But, when the demagnetization of the AP-FSPM’s PMs is taken into account, the torque density and torque per PM values of the AP-FSPM structure plummets. A complete full-load demagnetization analysis is done in order to get a better understanding of how the performance of the IMPM structure supersedes the AP-FSPM structure. 2D finite element analysis is used to extract the most important indexes of both topologies.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Rotation Exploration Transformer for Aerial Person Re-identification

Rotation Exploration Transformer for Aerial Person Re-identi...

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Lei Wang Quan Zhang Junyang Qiu Jianhuang Lai School of Computer Science and Engineering Sun Yat-sen University China Guangdong Province Key Laboratory of Information Security Technology China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education China Pazhou Lab (HuangPu) Guangzhou China

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

Aerial person re-identification (AReID) focuses on accurately matching target person images within a UAV camera network. Challenges arise due to the broad field of view and arbitrary movement of UAVs, leading to foreground target rotation and background style variation. Existing AReID methods have provided limited solutions for the former, while the latter remains largely unexplored. This paper propose a Rotation Exploration Vision Transformer (RoExViT) to tackle the aforementioned dual challenges. Specifically, we design Multiple Rotation Tokens (MRT) to explore diverse rotational representations at the feature level, addressing foreground target rotation. To handle background style variation, we propose Cross-Camera Similarity (CCS) loss to effectively minimize the view gap among different cameras. Furthermore, we propose Iteratively Adaptive Batch Construction (IABC) strategy to mitigate overfitting on small datasets. Extensive experiments show that our method outperforms the state-of-the-art methods on PRAI-1581 and UAV-Human while also exhibting outstanding performance on Market1501.

关键词： computer vision Transformers Cameras Autonomous aerial vehicles Identification of persons

来源：评论

学校读者我要写书评

暂无评论

Investigating the Use of Ray Tracing for Signal-Level Radar Simulation in Space Surveillance

Investigating the Use of Ray Tracing for Signal-Level Radar ...

引用

IEEE International Conference on Information Communication and Signal Processing (ICICSP)

作者： Mogamat Yaaseen Martin Simon Winberg Yunus Abdul Gaffar David Macleod Department of Electrical Engineering University of Cape Town Cape Town South Africa Advanced Computer Engineering Lab Centre for High Performance Computing Cape Town South Africa

The growing number of objects in the Low Earth Orbit is becoming increasingly concerning to astronomers and space missions - particularly due to the limitations in tracking accuracy due to the availability and placements of surveillance sensors. This paper connects to this issue, presenting the development of an open-source, ray-traced, signal-level pulsed radar simulator for use in exploring and planning space monitoring solutions without using real-time data feeds. The simulator was also developed around the use of the NVIDIA® OptiX™ engine to accommodate its ray-tracing features and accelerate performance. This was designed to aid astronomers and researchers in space situational awareness applications through the simulation of radar designs for orbital surveillance experiments. The developed tool was also compared against a more streamlined application that used point-model approximations for quick-look simulations, and the trade-offs between both simulators were evaluated. While the use of ray tracing resulted in significant speed costs, it was found that the algorithm also introduced more realistic results relative to point-model simulations - providing various advantages in scenarios involving shadowing and multiscatter.

关键词： Space vehicles Spaceborne radar Surveillance Space missions Space debris Ray tracing Radar tracking

来源：评论

学校读者我要写书评

暂无评论

Inserting anybody in diffusion models via celeb basis 23

Inserting anybody in diffusion models via celeb basis

引用

Proceedings of the 37th International Conference on Neural Information Processing Systems

作者： Ge Yuan Xiaodong Cun Yong Zhang Maomao Li Chenyang Qi Xintao Wang Ying Shan Huicheng Zheng School of Computer Science and Engineering Sun Yat-sen University and Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education China and Guangdong Key Laboratory of Information Security Technology and Tencent AI Lab Tencent AI Lab The Hong Kong University of Science and Technology School of Computer Science and Engineering Sun Yat-sen University and Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education China and Guangdong Key Laboratory of Information Security Technology

Exquisite demand exists for customizing the pretrained large text-to-image model, e.g. Stable Diffusion, to generate innovative concepts, such as the users themselves. However, the newly-added concept from previous customization methods often shows weaker combination abilities than the original ones even given several images during training. We thus propose a new personalization method that allows for the seamless integration of a unique individual into the pre-trained diffusion model using just one facial photograph and only 1024 learnable parameters under 3 minutes. So we can effortlessly generate stunning images of this person in any pose or position, interacting with anyone and doing anything imaginable from text prompts. To achieve this, we first analyze and build a well-defined celeb basis from the embedding space of the pre-trained large text encoder. Then, given one facial photo as the target identity, we generate its own embedding by optimizing the weight of this basis and locking all other parameters. Empowered by the proposed celeb basis, the new identity in our customized model showcases a better concept combination ability than previous personalization methods. Besides, our model can also learn several new identities at once and interact with each other where the previous customization model fails to. Project page is at: http://***. Code is at: https://***/ygtxr1997/CelebBasis.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Single Frame Lidar-Camera Calibration Using Registration of 3D Planes

Single Frame Lidar-Camera Calibration Using Registration of ...

引用

IEEE International Conference on Robotic Computing (IRC)

作者： Ashutosh Singandhupe Hung Manh La Quang Phuc Ha Department of Computer Science and Engineering Advanced Robotics and Automation (ARA) Lab University of Nevada Reno NV USA School of Electrical and Data Engineering University of Technology Sydney Australia

ISBN: (纸本)9781665472616

This work focuses on finding the extrinsic parameters (rotation and translation) between Lidar and an RGB camera sensor. We use a planar checkerboard and place it inside the Field-of-View (FOV) of both sensors, where we extract the 3D plane information of the checkerboard acquired from the sensor’s data. The plane coefficients extracted from the sensor’s data are used to construct a well-structured set of 3D points. These 3D points are then ’aligned,’ which gives the relative transformation between the two sensors. We use our proposed Correntropy Similarity Matrix Iterative Closest Point (CoSMICP) Algorithm to estimate the relative transformation. This work uses a single frame of the point cloud data acquired from the Lidar sensor and a single frame from the calibrated camera data to perform this operation. From the camera image, we use the projection of the calibration target’s corner points to compute the 3D points, and along the process, we calculate the 3D plane equation using the corner points. We evaluate our approach on a simulated dataset with complex environment settings, making use of the freedom to assess under multiple configurations. Through the obtained results, we verify our method under various configurations.

关键词： Point cloud compression Three-dimensional displays Laser radar Transmission line matrix methods Robot vision systems Cameras Real-time systems

来源：评论

学校读者我要写书评

暂无评论

Sentence-State LSTMs For Sequence-to-Sequence Learning 10th

Sentence-State LSTMs For Sequence-to-Sequence Learning

引用

10th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2021

作者： Bai, Xuefeng Li, Yafu Zhang, Zhirui Xu, Mingzhou Chen, Boxing Luo, Weihua Wong, Derek Zhang, Yue School of Engineering Westlake University Hangzhou China Alibaba DAMO Academy Hangzhou China NLP2CT Lab Department of Computer and Information Science University of Macau China Institute of Advanced Technology Westlake Institute for Advanced Study Hangzhou China

ISBN: (纸本)9783030884796

Transformer is currently the dominant method for sequence to sequence problems. In contrast, RNNs have become less popular due to the lack of parallelization capabilities and the relatively lower performance. In this paper, we propose to use a parallelizable variant of bi-directional LSTMs (BiLSTMs), namely sentence-state LSTMs (S-LSTM), as an encoder for sequence-to-sequence tasks. The complexity of S-LSTM is only O(n) as compared to O(n2) of Transformer. On four neural machine translation benchmarks, we empirically find that S-SLTM can achieve significantly better performances than BiLSTM and convolutional neural networks (CNNs). When compared to Transformer, our model gives competitive performance while being 1.6 times faster during inference. © 2021, Springer Nature Switzerland AG.

关键词： Neural machine translation

来源：评论

学校读者我要写书评

暂无评论

Empirical Study of Computational Intelligence Approaches for the Early Detection of Autism Spectrum Disorder 5th

Empirical Study of Computational Intelligence Approaches for...

引用

5th International Conference on Intelligent Computing and Applications, ICICA 2019

作者： Khatun, Mst. Arifa Ali, Md. Asraf Ahmed, Md. Razu Noori, Sheak Rashed Haider Sahayadhas, Arun Department of Computer Science and Engineering Daffodil International University Dhaka Bangladesh Department of Software Engineering Daffodil International University Dhaka Bangladesh Artificial Intelligence Research Lab Vels Institute of Science Technology and Advanced Studies Chennai India

ISBN: (纸本)9789811555657

The objective of the research is to develop a predictive model that can significantly enhance the detection and monitoring performance of Autism Spectrum Disorder (ASD) using four supervised learning techniques. In this study, we applied four supervised-based classification techniques to the clinical ASD data obtained from 704 patients. Then, we compared the four machine learning (ML) algorithms performance across tenfold cross-validation, ROC curve, classification accuracy, F1 measure, precision, recall, and specificity. The analysis findings indicate that Support Vector Machine (SVM) achieved the uppermost performance than the other classifiers in terms of accuracy (85%), f1 measure (87%), precision (87%), and recall (88%). Our work presents a significant predictive model for ASD that can effectively help the ASD patients and medical practitioners. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

A Complex Hermitian Positive Definite Manifold Embedding Transformer Network for Time-Varying Direction of Arrival Tracking

引用

IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Teng, Liping Wang, Qing Wang, Yanhui Guo, Qinghua Li, Wanqing Tianjin University School of Electrical and Information Engineering Tianjin300072 China Nantong University School of Information Science and Technology Nantong226019 China Science and Technology on Space Physics Laboratory Beijing100076 China University of Wollongong School of Electrical Computer and Telecommunications Engineering WollongongNSW2522 Australia University of Wollongong Advanced Multimedia Research Lab WollongongNSW2522 Australia

In this work, we address the challenge of stable and robust time-varying direction-of-arrival (DOA) tracking, where both the DOA trajectory and the number of sources change over time across different scenarios. We formulate the problem as a multi-label classification task and propose a novel solution leveraging Riemannian manifold geometry and advanced neural networks for sequential data processing. Specifically, we introduce the Complex Hermitian Positive Definite embedding Transformer (C-HPD-T) network, which learns statistical representations of covariance matrices. The C-HPD-T consists of an HPD module and a Transformer module. The HPD module learns an appropriate statistical representation and the complex Transformer module models the data temporally. In particular, in the C-HPD-T network, we build a complex singular value decomposition (SVD) module to ensure that complex structure is preserved during the calculation of each layer. Meanwhile, we design a Transformer-based sequential network to capture the temporal relationship of signals and for the time-varying DOAs. Through training the network with varying numbers of moving targets featuring diverse motion trajectories, the network demonstrates excellent performance and robustness against array imperfections. Extensive simulation results demonstrate its superior performance gains compared to existing methods. © 2015 IEEE.

关键词： Covariance matrix

来源：评论

学校读者我要写书评

暂无评论

The Strategy on Artificial Neural Networks for Predicting advanced Packaging Reliability Under Small Dataset

The Strategy on Artificial Neural Networks for Predicting Ad...

引用

International Conference on Electronics Packaging (ICEP)

作者： Qinghua Su Cadmus Yuan K.N. Chiang Taiwan Dept. of Power Mechanical Engineering Advanced Microsystem Packaging and Nano-Mechanics Research Lab National Tsing Hua University Hsinchu Taiwan R.O.C. Dept. of Mechanical and Computer-Aided Engineering Feng Chia University Taichung Taiwan R.O.C.

ISBN: (数字)9784991191176

ISBN: (纸本)9798350385908

Applying AI-assisted design on simulation (AI-DoS) requires sufficient training database that is generated by a validated, parametric nonlinear finite element model. This study focuses to investigate a training database design method to achieve the balance between the AI model training accuracy and the computational efforts of the FE model execution. Considering the importance of training data, we will use the K-Medoids to select data points for training set. Due to small data, ensemble learning is introduced to enhance the prediction performance of the ANN model.

关键词： Training Semiconductor device modeling Databases Computational modeling Training data Artificial neural networks Predictive models

来源：评论

学校读者我要写书评

暂无评论

Scalable Electrophysiology of Millimeter-Scale Animals with Electrode Devices

引用

Biomedical engineering Frontiers 2023年第1期4卷 3-20页

作者： Kairu Dong Wen-Che Liu Yuyan Su Yidan Lyu Hao Huang Nenggan Zheng John A.Rogers Kewang Nan College of Pharmaceutical Sciences Zhejiang UniversityHangzhou 310058China National Key Laboratory of Advanced Drug Delivery and Release Systems Zhejiang UniversityHangzhou 310058China College of Biomedical Engineering&Instrument Science Zhejiang UniversityHangzhou310027China Department of Gastroenterology Brigham and Women’s HospitalHarvard Medical SchoolBostonMA 02115USA College of Chemical and Biological Engineering Zhejiang UniversityHangzhou 310058China Qiushi Academy for Advanced Studies Zhejiang UniversityHangzhou 310027China College of Computer Science and Technology Zhejiang UniversityHangzhou 310027China State Key Lab of Brain-Machine Intelligence Zhejiang UniversityHangzhou 310058China CCAI by MOE and Zhejiang Provincial Government(ZJU) Hangzhou 310027China Querrey Simpson Institute for Bioelectronics Northwestern UniversityEvanstonIL 60208USA Department of Biomedical Engineering Northwestern UniversityEvanstonIL 60208USA Department of Materials Science and Engineering Northwestern UniversityEvanstonIL 60208USA Department of Mechanical Engineering Northwestern UniversityEvanstonIL 60208USA Jinhua Institute of Zhejiang University Jinhua 321299China

Millimeter-scale animals such as Caenorhabditis elegans,Drosophila larvae,zebrafish,and bees serve as powerful model organisms in the fields of neurobiology and *** methods exist for recording large-scale electrophysiological signals from these *** approaches often lack,however,real-time,uninterrupted investigations due to their rigid constructs,geometric constraints,and mechanical mismatch in integration with soft *** recent research establishes the foundations for 3-dimensional flexible bioelectronic interfaces that incorporate microfabricated components and nanoelectronic function with adjustable mechanical properties and multidimensional variability,offering unique capabilities for chronic,stable interrogation and stimulation of millimeter-scale animals and miniature tissue *** review summarizes the most advanced technologies for electrophysiological studies,based on methods of 3-dimensional flexible bioelectronics.A concluding section addresses the challenges of these devices in achieving freestanding,robust,and multifunctional biointerfaces.

关键词： offering recording millimeter

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：