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arXiv 2024年

作者： Yang, Jianyu Li, Nan Pan, Yuyao Yang, Jing Chen, Zhiming Cai, Han Wang, Yuliang Han, Chuankun Chen, Xingfan Liu, Cheng Hu, Huizhu State Key Laboratory of Extreme Photonics and Instrumentation College of Optical Science and Engineering Zhejiang University Hangzhou310027 China Research Center for Advanced Computational Sensing and Intelligent Processing Zhejiang Lab Hangzhou310000 China Beijing Aerospace Control Instrument Research Institute Beijing100854 China

As a typical application of photon momentum transfer, optical levitation systems are known for their ideal isolation from mechanical dissipation and thermal noise. These characters offer extraordinary potential for acceleration precision sensing and have attracted extensive attention in both fundamental and applied physics. Although considerable improvements of optical levitation accelerometers has been reported, the dynamic testing of the sensing performance remains a crucial challenge before the utilization in practical application scenarios. In this work, we present a dual-beam optical levitation accelerometer and demonstrate the test with dynamic inputs for the first time. An acceleration sensing sensitivity of 0.1µg and a measurement range of 1g are achieved. These advancements solidify the potential of optical levitation accelerometer for deployment in practical domains, including navigation, intelligent driving, and industrial automation, building a bridge between the laboratory systems and real-world applications. Copyright © 2024, The Authors. All rights reserved.

关键词： Momentum transfer

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Design of interval type-2 fuzzy logic controller for mobile wheeled inverted pendulum

Design of interval type-2 fuzzy logic controller for mobile ...

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World Congress on intelligent control and Automation (WCICA)

作者： MyongHyok Ri Jian Huang Songhyok Ri HyonSu Yun ChangSik Kim Department of Control Science KimChaek University of Technology Pyongyang Wuhan Democratic People's Republic of Korea Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan CHINA Department of Computer Science Hamhung University of Chemical Industry Hamhung Wuhan Democratic People's Republic of Korea Department of Computer Science KimChaek University of Technology Pyongyang Democratic People's Republic of Korea

ISBN: (纸本)9781467384155

In this paper, a novel interval type-2 fuzzy logic controller (IT2FLC) is proposed for controlling a mobile wheeled inverted pendulum(MWIP) with model uncertainties and external disturbances. The MWIP is a typical underactuated system which is generally composed of two subsystems, an invert pendulum and a mobile robot system. The IT2FLC proposed in this paper is composed of a balancing controller, a velocity controller and a yaw steering controller. The proposed integrated IT2FLC is linear combination of the three individual IT2FLCs which uses simplified type reduce method. The proposed controller has simple structure and requires less computation, also it is expected to have robustness to uncertainties and external disturbances in the practical implementation. Considering the model uncertainties and external disturbances, simulation results proved the effectiveness and robustness of the proposed IT2FLC compared with type-1 fuzzy logic controller (T1FLC).

关键词： Fuzzy logic Wheels Uncertainty Robustness Mobile communication control systems Automation

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Novel way achieving 3D reconstruction of actual human face using multi images

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Tien Tzu Hsueh Pao/Acta Electronica Sinica 2008年第4期36卷 661-666页

作者： Hou, Wen-Guang Chan, Tai-Wai Ding, Ming-Yue Image Processing and Intelligent Control Key Laboratory Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Industrial Centre Hong Kong Polytechnic University Hong Kong Hong Kong

A novel way achieving geometrical reconstruction of actual human face through projecting two types of texture on face in short time is advanced. The first type texture is stripe which is used to establish parallax grid between images. Taking into account of its results, the second type projecting texture is used to match by virtue of its abundant traits. After realizing geometrical reconstruction, the paper provides a general way about achieving actual texture reconstruction by the outer spherical surface surrounding object. In order to uniform color, it deals with parts of images in conjunct region and makes the color change meeting a certain function on condition of keeping their original information mostly. Results show this way can improve reconstruction quality and decrease complicacy of algorithm.

关键词： image reconstruction

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Boosting discriminative model for moving cast shadow detection

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Jisuanji Xuebao/Chinese Journal of Computers 2007年第8期30卷 1295-1301页

作者： Zha, Yu-Fei Chu, Ying Wang, Xun Ma, Shi-Ping Bi, Du-Yan Signal and Information Processing Laboratory Engineering College Air Force Engineering University Xi'an 710038 China Key Laboratory for Image Processing and Intelligent Control Institute of Pattern Recognition and Artificial Intelligence Huazhong Univ. of Sci. and Technol. Wuhan 430074 China

Moving cast shadow causes serious problem while segmenting and extracting foreground from image sequences, due to the misclassification of moving shadow as foreground. This paper proposes a Boosting discriminative model to eliminate cast shadow on Discriminative Random Fields (DRFs). The method combines different features for Boosting to discriminate cast shadow from moving objects, then temporal and spatial coherence of shadow and foreground are incorporated on Discriminative Random Fields and the problem can be solved by graph cut. Firstly, moving objects are obtained by background subtraction;secondly, shadow candidates can be derived through pre-processing moving objects, in terms of the shadow physical property;thirdly, color information and texture information is derived by comparing shadow and foreground points in current image with corresponding points in background image, which are selected as features for Boosting;finally, temporal and spatial coherence of shadow and foreground is employed on Discriminative Random Fields and discriminate shadow and foreground by graph cut accurately.

关键词： image processing

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Switched High-Gain Based Interval Observer Design for Harmonic Oscillator System

Switched High-Gain Based Interval Observer Design for Harmon...

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Chinese control Conference (CCC)

作者： Tianhang Ming Xiaoling Wang Bo Liu Housheng Su College of Automation & AI Nanjing University of Posts and Telecommunications Nanjing P. R. China Jiangsu Engineering Lab for IOT Intelligent Robots (IOTRobot) Nanjing China College of Information Engineering Minzu University of China Beijing P. R. China Key Laboratory of Image Processing and Intelligence Control of Ministry of Education Huazhong University of Science and Technology Wuhan P. R. China

In this paper, we revisit the interval observer design problem of harmonic oscillator system with unknown but bounded external disturbance and measurement noise. With the bounding information of the external disturbance and measurement noise, a high-gain interval observer is firstly defined and constructed for the harmonic oscillator system to realize the interval estimation on the state and the robust control of the system. Then, a switched high-gain interval observer is proposed to reduce the influence of the measurement noise for a tighter interval width on the state estimation. Finally, some numerical simulations are given to verify the theoretical results.

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A Self-Reproduction Hyperchaotic Map With Compound Lattice Dynamics

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2022年第10期69卷 10564-10572页

作者： Li, Yongxin Li, Chunbiao Zhang, Sen Chen, Guanrong Zeng, Zhigang Nanjing Univ Informat Sci & Technol Dept Informat & Commun Engn Nanjing 210044 Peoples R China Nanjing Univ Informat Sci & Technol Sch Artificial Intelligence Nanjing 210044 Peoples R China Nanjing Univ Informat Sci & Technol Collaborat Innovat Ctr Atmospher Environm & Equip Nanjing 210044 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence Inst Artificial Intelligence Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Educ Minist China Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China City Univ Hong Kong Dept Elect Engn Hong Kong 999077 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China

In this article, sinusoidal functions are introduced to a discrete map for hyperchaos generation and attractor self-reproduction. The constructed map shares a unique structure with controllable symmetry and conditional symmetry, which exhibits compound lattice dynamics, including 1-D and 2-D attractor growth. The direction of attractor growth can be controlled under polarity balance. STM32-based circuit realization verifies the results with numerical simulation and theoretical analysis. A pseudorandom number generator is built finally based on the newly proposed hyperchaotic map proving the high performance in application.

关键词： Chaotic communication Lattices Compounds Trajectory Generators Artificial intelligence Eigenvalues and eigenfunctions Attractor growth attractor self-reproduction (ASR) hyperchaotic map lattice dynamics

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Global Rice Multi-Class Segmentation Dataset (RiceSEG): A Comprehensive and Diverse High-Resolution RGB-Annotated images for the Development and Benchmarking of Rice Segmentation Algorithms

arXiv

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arXiv 2025年

作者： Zhou, Junchi Wang, Haozhou Kato, Yoichiro Nampally, Tejasri Rajalakshmi, P. Balram, M. Katsura, Keisuke Lu, Hao Mu, Yue Yang, Wanneng Gao, Yangmingrui Xiao, Feng Chen, Hongtao Chen, Yuhao Li, Wenjuan Wang, Jingwen Yu, Fenghua Zhou, Jian Wang, Wensheng Hu, Xiaochun Yang, Yuanzhu Ding, Yanfeng Guo, Wei Liu, Shouyang Engineering Research Center of Plant Phenotyping Ministry of Education Jiangsu Collaborative Innovation Center for Modern Crop Production Academy for Advanced Interdisciplinary Studies Sanya Institute of Nanjing Agricultural University Nanjing Agricultural University Nanjing China Graduate School of Agricultural and Life Sciences The University of Tokyo Tokyo Japan Department of Artificial Intelligence Indian Institute of Technology Hyderabad India Department of Electrical Engineering Indian Institute of Technology Hyderabad India Institute of Biotechnology Professor Jayashankar Telangana Agricultural State University Hyderabad India Graduate School of Agriculture Kyoto University Kyoto Japan Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China National Key Laboratory of Crop Genetic Improvement National Center of Plant Gene Research Hubei Key Laboratory of Agricultural Bioinformatics Huazhong Agricultural University Wuhan China State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China the Institute of Agricultural Resources and Regional Planning Chinese Academy of Agricultural Sciences Beijing China Center for Geospatial Information Shenzhen Institutes of Advanced Technology Chinese Academy of Science Shenzhen China School of Information and Electrical Engineering Shenyang Agricultural University Shenyang China Rice Research Institute Jilin Academy of Agricultural Sciences Changchun China Institute of Crop Sciences National Key Facility for Crop Gene Resources and Genetic Improvement Chinese Academy of Agricultural Sciences Beijing China Yuan Long Ping High-Tech Agriculture Co. Ltd. Changsha China

Developing computer vision–based rice phenotyping techniques is crucial for precision field management and accelerating breeding, thereby continuously advancing rice production. Among phenotyping tasks, distinguishing image components is a key prerequisite for characterizing plant growth and development at the organ scale, enabling deeper insights into eco-physiological processes. However, due to the fine structure of rice organs and complex illumination within the canopy, this task remains highly challenging, underscoring the need for a high-quality training dataset. Such datasets are scarce, both due to a lack of large, representative collections of rice field images and the time-intensive nature of annotation. To address this gap, we established the first comprehensive multi-class rice semantic segmentation dataset, RiceSEG. We gathered nearly 50,000 high-resolution, ground-based images from five major rice-growing countries (China, Japan, India, the Philippines, and Tanzania), encompassing over 6,000 genotypes across all growth stages. From these original images, 3,078 representative samples were selected and annotated with six classes (background, green vegetation, senescent vegetation, panicle, weeds, and duckweed) to form the RiceSEG dataset. Notably, the sub-dataset from China spans all major genotypes and rice-growing environments from the northeast to the south. Both state-of-the-art convolutional neural networks and transformer-based semantic segmentation models were used as baselines. While these models perform reasonably well in segmenting background and green vegetation, they face difficulties during the reproductive stage, when canopy structures are more complex and multiple classes are involved. These findings highlight the importance of our dataset for developing specialized segmentation models for rice and other crops. The RiceSEG dataset is publicly available at ***. © 2025, CC BY.

关键词： Semantic Segmentation

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Array P systems with parallel rewriting and tables of context-free rules

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Journal of Computational and Theoretical Nanoscience 2016年第6期13卷 3636-3642页

作者： Pan, Linqiang Song, Bosheng Isawasan, Pradeep Subramanian, K.G. School of Electric and Information Engineering Zhengzhou University of Light Industry Zhengzhou Henan450002 China Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan Hubei430074 China 32 Jalan Anson Penang10400 Malaysia Department of Mathematics and Computer Science Faculty of Science Liverpool Hope University LiverpoolL16 9JD United Kingdom

The two areas of picture languages and membrane computing were linked by array-rewriting P system in which array objects and context-free array-rewriting rules are used in order to generate picture languages. While rewriting arrays in the array-rewriting P system is in a sequential manner, parallel array P system (PAP) involves rewriting of arrays in the regions in parallel in order to generate picture languages. A variant of PAP, known as tabled array P system (TPAP), uses sets of context-free array-rewriting rules, called tables of rules. Generative power of TPAP in comparison with PAP and certain other kinds of picture array generating mechanisms are investigated. Copyright © 2016 American Scientific Publishers. All rights reserved.

关键词： Context free languages

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Asymmetry in cross-hippocampal connectivity in unilateral mesial temporal lobe epilepsy

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EPILEPSY RESEARCH 2015年 118卷 14-21页

作者： Li, Hong Fan, Wenliang Yang, Jie Song, Shuyan Liu, Yuan Lei, Ping Shrestha, Lochan Mella, Grace Chen, Wei Xu, Haibo Huazhong Univ Sci & Technol Tongji Med Coll Union Hosp Dept Radiol Wuhan 430022 Peoples R China Massachusetts Gen Hosp Dept Commun Sci & Disorders Inst Hlth Profess Boston MA 02114 USA Huazhong Univ Sci & Technol Educ Minist China Key Lab Image Proc & Intelligent Control Sch Life Sci & Technol Wuhan 430074 Peoples R China Tongji Univ Tonsil Hosp Dept Radiol Sch Med Shanghai Peoples R China First Peoples Hosp Yibin Radiol & Med Imaging Ctr Sichuan 644000 Peoples R China Wuhan Univ Zhongnan Hosp Dept Radiol Wuhan 430071 Peoples R China

Mesial temporal lobe epilepsy (mTLE) is mostly characterized by hippocampal sclerosis (HS) changes. Although considerable progress has been made in understanding the altered functional network of mTLE patients, whether one side of the abnormal hippocampal (HP) structure will affect the other healthy side of the hippocampal network is still unclear. Here, we used a seed-based method to explore the commonly alterative hippocampal network in mTLE patients by comparing the bilateral hippocampal network of unilateral mTLE patients with healthy control participants. We observed that both sides of the hippocampal network in unilateral mTLE patients were changed independent of the affected or "healthy" side, which may suggest a common plasticity network for both sides of hippocampal sclerosis mesial temporal lobe epilepsy patients. Furthermore, using the HP as the ROT, we found that the functional connectivity of the intra-HP in the left mTLE-HS group was moderately positively correlated with the duration of the disease, while a strong negative correlation between functional connectivity of the intra-HP and duration were detected in the right mTLE-HS group, which suggested that it was easier for the right HP than the left HP to communicate with the contralateral HP according to the progression of mTLE disease because the hippocampus plays different roles in the communication and compensatory mechanism associated with the contralateral side of the hemisphere. We hope that this potential relevance may help us to better characterize mTLE with hippocampal sclerosis and ultimately assist in providing a better diagnosis and more accurate invasive treatments of mTLE. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Mesial temporal lobe epilepsy Hippocampal network Resting state functional connectivity Brain plasticity

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Understanding the Robustness of 3D Object Detection with Bird’s-Eye-View Representations in Autonomous Driving

arXiv

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arXiv 2023年

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 Dept. of Comp. Sci. and Tech. Institute for AI THBI Lab BNRist Center Tsinghua University China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education School of Computer Science and Technology Anhui University Information Materials and Intelligent Sensing Laboratory of Anhui Province China SAIC Motor AI Lab China Zhongguancun Laboratory China

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-LiDAR fusion 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. Code available at https: //***/zzj403/BEV_Robust. Copyright © 2023, The Authors. All rights reserved.

关键词： Birds

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