检索结果-内蒙古大学图书馆

Computer, Vision and intelligent technology (ICCVIT), International Conference on

作者： Peng Zhou Liqing Geng Genghuang Yang Liming Chen School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin China Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin University of Technology and Education Tianjin China Fitow (Tianjin) Detection Technology Co.Ltd Tianjin China

ISBN: (数字)9798331540043

ISBN: (纸本)9798331540050

Address the challenges posed by the diverse range of potato fruit defects, which encompass difficulties in detection and limited accuracy, an improved YOLOv8 potato disease detection algorithm is proposed. Firstly, for the lack of spatial information capturing ability of the original YOLOv8 model, the DRB idea is introduced to improve the C2f module, and then the original C2f module is improved by the improved C2f-DRB module. Secondly, for the problem that small targets of potato diseases are not easy to be detected, the CARAFE up-sampling operator is introduced to improve the model's ability of extracting features of the disease, and to enhance the effect of the disease detection. Finally, the original IoU loss function of the model is improved using the Inner IoU loss function, which enhances the generalization ability of the model. Relevant comparison experiments were constructed for ten kinds of diseased potatoes, and the results showed that the improved YOLOv8 algorithm improved 2.4%, 1.7%, and 1.5% in precision, recall, and mAP50, respectively, which proved the proposed algorithm had better performance, and verified the effectiveness and feasibility of the proposed algorithm.

关键词： Computer vision Accuracy Feature extraction detection algorithms Diseases

来源：评论

学校读者我要写书评

暂无评论

Petal-like Bessel beam based high-resolution optical ranging for hypersonic turbulence

引用

Optics Express 2025年第12期33卷 26174-26186页

作者： Yujie Feng Chaoxu Chen Wei Chen Qingqing Deng Yong Bo Lixia Yang Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui University Hefei 230601 China Key Laboratory for Information Science of Electromagnetic Waves (MoE) Department of Communication Science and Engineering Fudan University Shanghai 200433 China Jianghuai Advance Technology Center Hefei 230000 China

For in-flight hypersonic vehicles, intense friction with the air and high-temperature ionization effects generate plasma sheath turbulence (PST) around the target, significantly impeding electromagnetic wave transmission and presenting challenges for target detection. Conventional time-domain ranging methods, such as the time-of-flight and pulse-based methods, exhibit limitations in PST. A spatial-domain ranging method is developed utilizing the unique propagation characteristics of petal-like Bessel beams. These beams, generated through the coherent superposition of vortex phases, exhibit high stability under PST conditions. By leveraging the relationship between the rotation angle of the petal-like Bessel beam and the propagation distance, high-precision ranging is achieved. Additionally, an angle recognition neural network (ARNN) is introduced to improve accuracy in turbulent environments, overcoming the limitations of traditional correlation intensity methods. The ARNN demonstrates high prediction accuracy and strong generalization capabilities. Our method achieves over 90% accuracy with a resolution of 1 mm across various plasma turbulence conditions characterized by refractive index fluctuation variance 〈Δ n 2 〉 and different distance resolutions. These findings indicate a viable approach for target detection in complex media such as PST.

关键词： Diffraction limit Free space optics Neural networks Optical systems Refractive index Scintillation index

来源：评论

学校读者我要写书评

暂无评论

Natural Human Skin‑Inspired Wearable and Breathable Nanofiber‑based Sensors with Excellent Thermal Management Functionality

引用

Advanced Fiber Materials 2024年第6期6卷 1955-1968页

作者： Peng Wang Xiaodan Li Guifen Sun Guoqing Wang Qing Han Chuizhou Meng Zhonghe Wei Yang Li School of Mechanical Engineering University of JinanJinan 250022China School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China State Key Laboratory for Reliability and Intelligence of Electrical Equipment Engineering Research Center of Ministry of Education for Intelligent Rehabilitation Device and Detection TechnologyHebei Key Laboratory of Smart Sensing and Human‑Robot InteractionSchool of Mechanical EngineeringHebei University of TechnologyTianjin 300401China Shandong Provincial Key Laboratory of Network‑Based Intelligent Computing School of Information Science and EngineeringUniversity of JinanJinan 250022China Network Information Center Department of Computer ScienceQilu University of Technology(Shandong Academy of Sciences)Jinan 250353China School of Integrated Circuits Shandong UniversityJinan 250101China

Wearable sensors have been rapidly developed for application in various human monitoring ***,the wearing comfort and thermal properties of these devices have been largely ignored,and these characteristics urgently need to be ***,we develop a wearable and breathable nanofiber-based sensor with excellent thermal management functionality based on passive heat preservation and active Joule heating *** multifunctional device consists of a micropatterned carbon nanotube(CNT)/thermoplastic polyurethane(TPU)nanofiber electrode,a microporous ionic aerogel electrolyte and a microstructured Ag/TPU nanofiber *** to the presence of a supercapacitive sensing mechanism and the appli-cation of microstructuration,the sensor shows excellent sensing performance,with a sensitivity of 24.62 ***,due to the overall porous structure and hydrophobicity of TPU,the sensor shows good breathability(62 mm/s)and water repellency,with a water contact angle of 151.2°.In addition,effective passive heat preservation is achieved by combining CNTs with high solar absorption rates(85%)as the top layer facing the outside,aerogel with a low thermal conductivity(0.063 W m-1 k-1)as the middle layer for thermal insulation,and Ag with a high infrared reflectance rate as the bottom layer facing the *** warming,this material yields a higher temperature than ***,the active Joule heat-ing effect is realized by applying current through the bottom resistive electrode,which can quickly increase the temperature to supply controlled warming on *** proposed wearable and breathable sensor with tunable thermal properties is promising for monitoring and heat therapy applications in cold environments.

关键词： Wearable sensor Breathable Personal thermal management Electrospun nanofibers Joule heating

来源：评论

学校读者我要写书评

暂无评论

HSI-MFormer: Integrating Mamba and Transformer Experts for Hyperspectral Image Classification

引用

IEEE Transactions on Geoscience and Remote sensing 2025年 63卷

作者： He, Yan Tu, Bing Liu, Bo Li, Jun Plaza, Antonio Institute of Optics and Electronics State Key Laboratory Cultivation Base of Atmospheric Optoelectronic Detection and Information Fusion Jiangsu International Joint Laboratory on Meteorological Photonics and Optoelectronic Detection Jiangsu Engineering Research Center for Intelligent Optoelectronic Sensing Technology of Atmosphere Nanjing University of Information Science and Technology Nanjing210044 China China University of Geosciences Faculty of Computer Science Wuhan430074 China University of Extremadura Hyperspectral Computing Laboratory Department of Technology of Computers and Communications Escuela Politecnica 10003 Spain

Hyperspectral image (HSI) classification is fundamental to numerous remote sensing applications, enabling detailed analysis of material properties and environmental conditions. Recent Mamba built upon selective state space models (SSMs) (S6) have demonstrated exceptional advantages in long-range sequence modeling with linear computational efficiency, while Transformer based on self-attention mechanisms is particularly adept at capturing short-range dependencies. To leverage the complementary strengths of these models, this article introduces a novel hybrid Mamba-Transformer framework (HSI-MFormer), effectively exploring the multiscale properties of hyperspectral data for HSI classification. Initially, a multiscale token generation (MTG) module is developed, which converts the HSI cube into multiple spatial-spectral token groups across different scales. To adequately capture fine-grained multiscale spatial-spectral patterns, an inner-scale transformer expert (ITE) is designed, which incorporates grouped self-attention operations to perform short-range sequence modeling within token groups at each scale. Meanwhile, a cross-scale Mamba expert (CME) is introduced, which integrates a cross-scale serialization mechanism and bidirectional Mamba block for long-range sequence modeling, further exploring the interactions and complementarity between token groups across different scales. Several hybrid strategies for integrating the ITE and CME are investigated to maximize their complementarity, including parallel, interval, and serial structures. Extensive experiments demonstrate that the proposed HSI-MFormer significantly outperforms the state-of-the-art Transformer-based and Mamba-based HSI classification methods. © 1980-2012 IEEE.

关键词： Image classification

来源：评论

学校读者我要写书评

暂无评论

Hyperuniform Radiation-Scattering Meta-Device for Scattering Suppression at Grazing-Incidence

引用

IEEE Antennas and Wireless Propagation Letters 2025年

作者： Wu, Xiong Bin Li, Hai Fan Yu Zhang, Hong Li, Jia Chen Xiong, Wei Zhou, Yong Jin Zhou, Xiao Yang Shanghai University Shanghai Collaborative Innovation Center of Intelligent Sensing Chip Technology School of Communication and Information Engineering Shanghai200444 China Jiangsu Cyberspace Science and Technology Co. Ltd. Nanjing211111 China Southeast University State Key Laboratory of Millimeter Waves Institute of Electromagnetic Space Nanjing210096 China Suzhou Laboratory Suzhou215164 China

Low-scattering periodic antenna arrays have been fully investigated in terms of their scattering properties under normal incidence. However, strong scattering can also occur due to diffraction peaks generated by periodic structures under grazing-incidence. In this paper, we present a hyperuniform radiation-scattering meta-device (HRSMD) that effectively maintains in-band radiation while reducing out-of-band scattering at grazing-incidence. The proposed unit consists of a U-shaped antenna and a 5×5 meta-atom array loaded with 100 Ω resistors. A hyperuniform distribution is introduced to arrange all units, effectively suppressing diffraction peaks caused by a periodic array under grazing-incidence. The proposed HRSMD behaves like a periodic array while resembling a random array with disordered spatial configuration. The fabricated sample shows a maximum measured gain of 16 dBi at 3 GHz, maintaining comparable radiation performance to a periodic array with the same aperture size. Additionally, we have fabricated a low-scattering carrier to investigate scattering performance of the HRSMD at grazing-incidence. Compared to the periodic array, the HRSMD effectively reduces the radar cross section (RCS) by an average of 6 dB (horizontal polarization) and 8 dB (vertical polarization) under grazing-incidence from 8 GHz to 12 GHz. At specific frequencies, the maximum RCS reduction reaches 26 dB and 31 dB for horizontal and vertical polarizations, respectively. The proposed HRSMD has significant potential for stealth applications involving periodic/non-periodic arrays at grazing-incidence. © 2002-2011 IEEE.

关键词： Antenna radiation

来源：评论

学校读者我要写书评

暂无评论

CA-LOSS: A Cosine Affinity Loss for Imbalanced SAR Ship Classification

CA-LOSS: A Cosine Affinity Loss for Imbalanced SAR Ship Clas...

引用

IEEE International Symposium on Geoscience and Remote sensing (IGARSS)

作者： Nishang Xie Mingkang Xiong Feiming Wei Tao Zhang Zhen Yang Wenxian Yu Shanghai Key Laboratory of Intelligent Sensing and Recognition Shanghai Jiao Tong University Shanghai China Midea Group Midea Corporate Research Center Foshan China School of Communication and Electronics Jiangxi Science and Technology Normal University Nanchang China

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

To address the problem of imbalanced datasets in SAR ship classification, this paper presents a novel cosine affinity (CA) loss that enhances the Gaussian affinity (GA) loss. The CA loss focuses on the angular relationship between feature vectors, prioritizing their direction over their magnitude, which is advantageous for high-dimensional space analysis. In addition, class weights are incorporated to compute weighted distances. Importantly, the proposed CA loss does not increase the computational complexity of algorithm, nor does it lead to overfitting problems associated with data-level techniques. Through various experiments, its effectiveness has been demonstrated by achieving the highest F1 score and recall compared to other existing loss functions, highlighting its superior ability to classify minority classes in FUSARShip.

关键词： Geoscience and remote sensing Deep architecture Benchmark testing Vectors Robustness Classification algorithms Marine vehicles

来源：评论

学校读者我要写书评

暂无评论

Real-Time of Channel Temperature Monitoring of P-Gan Hemts Based on Gate Leakage Current

SSRN

引用

SSRN 2023年

作者： Yin, Luqiao Wu, Shuang Ren, Kailin Zhang, Wenkui Zhang, Jianhua School of Microelectronics Shanghai University Shanghai200444 China Shanghai Key Laboratory of Chips and Systems for Intelligent Connected Vehicle Shanghai University Shanghai200444 China Shanghai Collaborative Innovation Center of Intelligent Sensing Chip Technology Shanghai University Shanghai200444 China Key Laboratory of Advanced Display and System Applications Ministry of Education Shanghai University Shanghai200444 China

The thermal response of Lateral GaN-based High Electron Mobility Transistor is much faster than that of Si-based power devices, owing to its higher power density. This makes temperature-related effects even more critical for GaN HEMTs, highlighting the necessity of monitoring their operating temperature to improve the efficiency and reliability of power circuits. In this article, a real-time monitoring method for channel temperature of p-GaN HEMTs using gate leakage current as a medium is proposed. The dependence of gate current on temperature is demonstrated by electro-thermal TCAD simulation on the reference p-GaN HEMT structure. An improved gate driver circuit is proposed that integrates a monitoring circuit utilizing the current amplification capability of bipolar transistors and an RC integrator network. The efficiency of the proposed solution is confirmed through SPICE electrothermal simulations and experimental validation on commercially available devices. In conclusion, the implementation of the monitoring circuit has been proved effective, offering a promising pathway to improve the reliability of p-GaN HEMTs. © 2023, The Authors. All rights reserved.

关键词： High electron mobility transistors

来源：评论

学校读者我要写书评

暂无评论

Understanding the Robustness of 3D Object detection with Bird'View Representations in Autonomous Driving

Understanding the Robustness of 3D Object Detection with Bir...

引用

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023

作者： Zhu, Zijian Zhang, Yichi Chen, Hai Dong, Yinpeng Zhao, Shu Ding, Wenbo Zhong, Jiachen Zheng, Shibao Institute of Image Communication and Network Engineering Shanghai Jiao Tong University China Institute for Ai Tsinghua University BNRist Center Thbi Lab Dept. of Comp. Sci. and Tech. China School of Computer Science and Technology Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Information Materials and Intelligent Sensing Laboratory of Anhui Province China Saic Motor Ai Lab Zhongguancun Laboratory China

ISBN: (纸本)9798350301298

3D object detection is an essential perception task in autonomous driving to understand the environments. The Bird's-Eye-View (BEV) representations have significantly improved the performance of 3D detectors with camera inputs on popular benchmarks. However, there still lacks a systematic understanding of the robustness of these vision-dependent BEV models, which is closely related to the safety of autonomous driving systems. In this paper, we evaluate the natural and adversarial robustness of various representative models under extensive settings, to fully understand their behaviors influenced by explicit BEV features compared with those without BEV. In addition to the classic settings, we propose a 3D consistent patch attack by applying adversarial patches in the 3D space to guarantee the spatiotemporal consistency, which is more realistic for the scenario of autonomous driving. With substantial experiments, we draw several findings: 1) BEV models tend to be more stable than previous methods under different natural conditions and common corruptions due to the expressive spatial representations;2) BEV models are more vulnerable to adversarial noises, mainly caused by the redundant BEV features;3) Camera-LiDARfusion models have superior performance under different settings with multi-modal inputs, but BEV fusion model is still vulnerable to adversarial noises of both point cloud and image. These findings alert the safety issue in the applications of BEV detectors and could facilitate the development of more robust models. © 2023 IEEE.

关键词： Autonomous driving

来源：评论

学校读者我要写书评

暂无评论

Heat transfer simulation of optogenetics-LED based on microchannel heat dissipation

Heat transfer simulation of optogenetics-LED based on microc...

引用

2024 International Conference on Optoelectronic Information and Computer Engineering, OICE 2024

作者： Liu, Lusheng Le, Song Zhang, Yuan Zhang, Jing Wang, Aiping Bin, Jianxiong Niu, Lan Zhang, Lihua Kang, Xiaoyang Laboratory for Neural Interface and Brain Computer Interface Engineering Research Center of AI & Robotics Ministry of Education Shanghai Engineering Research Center of AI & Robotics MOE Frontiers Center for Brain Science State Key Laboratory of Medical Neurobiology Institute of AI and Robotics Academy for Engineering & Technology Fudan University Shanghai200433 China Ji Hua Laboratory Guangdong Province Foshan528200 China Yiwu Research Institute of Fudan University Zhejiang Yiwu City322000 China Research Center for Intelligent Sensing Zhejiang Lab Hangzhou311121 China

ISBN: (纸本)9781510682504

Optogenetics technology has greatly promoted the development of neuroscience. Flexible gene manipulation tools and sensitive light activation methods have provided convenience for neural function research. However, the thermal effect generated in the process of light stimulation affects the activation of neurons by optogenetic technology, which makes the results of light-activated light-sensitive proteins to generate neural currents inaccurate. Here, we established an in vivo activation model of LED-based optogenetic technology through simulation and analyzed the thermal effect produced by it. We propose to use microchannels to dissipate heat from implanted devices, reducing the thermal effect of light stimulation for neural activation. Through simulation, we propose the use of the vortex-like and cobweb-like microchannels for heat dissipation, which can control the temperature rise within 0.28K and 0.31K, respectively. © 2024 SPIE.

关键词： Heat losses

来源：评论

学校读者我要写书评

暂无评论

SAR Aircraft detection based on Scattering Enhancement and Location Attention network

SAR Aircraft Detection based on Scattering Enhancement and L...

引用

Signal, Information and Data Processing (ICSIDP), IEEE International Conference on

作者： Bocheng Huang Sinong Quan Tao Zhang Feiming Wei Zhen Yang Shanghai Key Laboratory of Intelligent Sensing and Recognition Shanghai Jiao Tong University China School of Electronic Science and Engineering National University of Defense Technology Changsha China School of Communication and Electronics Jiangxi Science and Technology Normal University Nanchang China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Due to the interference caused by the complex background and the discreteness of aircraft scattering, the task of detecting aircraft in synthetic aperture radar (SAR) images remains a challenging one. To address these problems, a novel method named scattering enhancement and location attention network (SELANet) is here proposed to detect aircraft via combining traditional image processing and deep learning together. At first, a scattering information enhancement module (SIEM) is proposed to highlight the scattering points of aircraft targets. Moreover, to more effectively focus on the location of aircraft targets, a spatial location attention module (SLAM) is further designed. Experiments are performed on the SADD dataset and the results indicate that SELANet is more apt for aircraft detection. On average, the Precision, Recall, and F1-score values are respectively 3.6%, 2.9%, and 3.2% higher than the baseline of standard YOLOv8s algorithm.

关键词： Simultaneous localization and mapping Image processing Scattering Radar detection Interference Radar signal processing Radar polarimetry Aircraft Synthetic aperture radar Standards

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：