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Method for the real-time detection of tomato ripeness using a phenotype robot and RP-YolactEdge

International Journal of Agricultural and Biological Engineering 2024年第2期17卷 200-210页

作者： Yuanqiao Wang Wenbo Gou Chuanyu Wang Jiangchuan Fan Weiliang Wen Xianju Lu Xinyu Guo Chunjiang Zhao College of Information Engineering Northwest A&F UniversityYangling 712100ShaanxiChina China National Engineering Research Center for Information Technology in Agriculture(NERCITA) Beijing 100097China Beijing Key Laboratory of Digital Plant Beijing Research Center for Information Technology in AgricultureBeijing 100097China Beijing PAIDE Science and Technology Development Co. Ltd.Beijing 100097China

In order to address the challenge of non-destructive detection of tomato fruit ripeness in controlled environments,this study proposed a real-time instance segmentation method based on the edge *** method combined the principles of phenotype robots and machine vision based on deep learning.A compact and remotely controllable phenotype detection robot was employed to acquire precise data on tomato *** video data were then processed by using an efficient backbone and the FeatFlowNet structure for feature extraction and analysis of key-frame to non-key-frame mapping from video *** enhance the diversity of training datasets and the generalization of the model,an innovative approach was chosen by using random enhancement ***,the PolyLoss optimization technique was applied to further improve the accuracy of the ripeness multi-class detection *** validation,the method of this study achieved real-time processing speeds of 90.1 fps(RTX 3070Ti)and 65.5 fps(RTX 2060 S),with an average detection accuracy of 97%compared to manually measured *** is more accurate and efficient than other instance segmentation models according to actual testing in a ***,the results of this research can be deployed in edge devices and provide technical support for unmanned greenhouse monitoring devices or fruit-picking robots in facility environments.

关键词： instance segmentation phenotype robot tomato greenhouse-based plant phenotyping ripeness detection

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Spatiotemporal characteristics and remote sensing estimation of colored dissolved organic matter around the Leizhou Peninsula

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Journal of Oceanology and Limnology 2023年第4期41卷 1405-1424页

作者： Dongyang FU Shiyun WEI Guo YU Yafei LUO Huabing XU Zhaoguang CHEN College of Electronic and Information Engineering Guangdong Ocean UniversityZhanjiang 524088China Guangdong Provincial Engineering and Technology Research Center of Marine Zhanjiang 524088China

Colored dissolved organic matter(CDOM)is an important optically active substance in marine *** biochemical conservatism makes it an important indicator to offshore pollution *** the content,composition,and diffusion process of CDOM is a good approach to analyze the terrestrial input,optical properties,and ecological environment of offshore *** spatiotemporal characteristics of CDOM around the Leizhou Peninsula were analyzed based on field observation data collected in the autumn 2020 and spring 2021,and an empirical inversion model of the ag(355)(absorption coefficient at 355 nm)and spectral slope(Sg)(g stands for gelbstoff/gilvin,which is called CDOM)based on Sentinel-3A ocean and land color instrument(OLCI)images was *** results show(1)the order of average ag(355)value around the Leizhou Peninsula was east coast(0.503/m)>Qiongzhou Strait(0.502/m)>west coast(0.365/m);(2)the best band combinations of CDOM inversion in spring and autumn were(B4+B11)/B3 and(B7-B1)/B6(B stands for the band of spectral images),and the final inversion results are close to the measured results,indicating that the model has good accuracy;(3)the S_(g)value of the CDOM absorption spectrum was fitted to the hyperbolicexponential *** fitting accuracy of the model was higher than those of the exponential model and the hyperbolic model,and the best S_(g)inversion model was constructed by selecting Sg(275-295)and Sg(250-295)in spring and autumn;(4)the spatial distributions of ag(355)and S_(g)were inverted,and CDOM in the waters around the Leizhou Peninsula originated from terrestrial organic matter carried by coastal aquaculture zones and runoff in the northeast Zhanjiang and the northern Beibu Gulf.

关键词： colored dissolved organic matter(CDOM) ocean and land color instrument(OLCI) spectral slope hyperbolic-exponential model inversion

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Constraints Separation Based Evolutionary Multitasking for Constrained Multi-Objective Optimization Problems

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1819-1835页

作者： Kangjia Qiao Jing Liang Kunjie Yu Xuanxuan Ban Caitong Yue Boyang Qu Ponnuthurai Nagaratnam Suganthan School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou 450001China School of Electrical Engineering and Automation Henan Institute of TechnologyXinxiang 453003China School of Electronic and Information Zhongyuan University of TechnologyZhengzhou 450007China KINDI Center for Computing Research College of EngineeringQatar UniversityDoha 999043Qatar

Constrained multi-objective optimization problems(CMOPs)generally contain multiple constraints,which not only form multiple discrete feasible regions but also reduce the size of optimal feasible regions,thus they propose serious challenges for *** all constraints,some constraints are highly correlated with optimal feasible regions;thus they can provide effective help to find feasible Pareto ***,most of the existing constrained multi-objective evolutionary algorithms tackle constraints by regarding all constraints as a whole or directly ignoring all constraints,and do not consider judging the relations among constraints and do not utilize the information from promising single ***,this paper attempts to identify promising single constraints and utilize them to help solve *** be specific,a CMOP is transformed into a multitasking optimization problem,where multiple auxiliary tasks are created to search for the Pareto fronts that only consider a single constraint ***,an auxiliary task priority method is designed to identify and retain some high-related auxiliary tasks according to the information of relative positions and dominance ***,an improved tentative method is designed to find and transfer useful knowledge among *** results on three benchmark test suites and 11 realworld problems with different numbers of constraints show better or competitive performance of the proposed method when compared with eight state-of-the-art peer methods.

关键词： Constrained multi-objective optimization(CMOPs) evolutionary multitasking knowledge transfer single constraint.

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Kinship verification based on multi-scale feature fusion

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Multimedia Tools and Applications 2024年第40期83卷 88069-88090页

作者： Yan, Chunman Liu, Yanling Engineering Research Center of Gansu Province for Intelligent Information Technology and Application School of Physics and Electronic Northwest Normal University Lanzhou730070 China School of Physics and Electronic Northwest Normal University Lanzhou730070 China

Recent advancements in kinship verification research suggest that extracting suitable face kinship features is the key to solving this problem. Due to the emergence of deep learning, most of the existing methods for kinship verification use a convolutional neural network-based approach to perform the extraction of the overall feature information in the image, thus ignoring the local detail information in the image, resulting in incomplete extracted feature information. To address this problem, this paper proposes a method for kinship verification using extracted multi-scale features and fusion. Firstly a lightweight backbone framework based on convolutional neural network is constructed by stacking the designed residual block network several times. Second, the two convolutional neural networks with shared weight arguments are used for extracting features at different scales and fusing them for feature fusion with a view to better providing global contextual information about the kinship face images. Finally, the channel and spatial attention mechanisms are embedded in the feature extraction network to improve the ability of the network to extract feature information. Experiments are conducted on two widely used face kinship datasets, KinFaceW-I and KinFaceW-II, and the proposed method achieves an average accuracy of 83.85% and 91.75% for kinship verification, which verifies that the measures taken in this paper have better validation properties in kinship. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Convolutional neural networks

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Multi-Agent Deep Reinforcement Learning for Cross-Layer Scheduling in Mobile Ad-Hoc Networks

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China Communications 2023年第8期20卷 78-88页

作者： Xinxing Zheng Yu Zhao Joohyun Lee Wei Chen Department of Electronic Engineering and Beijing National Research Center for Information Science and Technology Tsinghua UniversityBeijing 100084China Department of Electrical and Electronic Engineering Hanyang UniversityAnsan 15588South Korea

Due to the fading characteristics of wireless channels and the burstiness of data traffic,how to deal with congestion in Ad-hoc networks with effective algorithms is still open and *** this paper,we focus on enabling congestion control to minimize network transmission delays through flexible power *** effectively solve the congestion problem,we propose a distributed cross-layer scheduling algorithm,which is empowered by graph-based multi-agent deep reinforcement *** transmit power is adaptively adjusted in real-time by our algorithm based only on local information(i.e.,channel state information and queue length)and local communication(i.e.,information exchanged with neighbors).Moreover,the training complexity of the algorithm is low due to the regional cooperation based on the graph attention *** the evaluation,we show that our algorithm can reduce the transmission delay of data flow under severe signal interference and drastically changing channel states,and demonstrate the adaptability and stability in different *** method is general and can be extended to various types of topologies.

关键词： Ad-hoc network cross-layer scheduling multi agent deep reinforcement learning interference elimination power control queue scheduling actorcritic methods markov decision process

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MEMS and MOEMS Gyroscopes: A Review

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Photonic Sensors 2023年第4期13卷 73-98页

作者： Wenyi HUANG Xing YAN Sengyu ZHANG Zhe LI Jamal NAHASSAN Dingwei CHEN Guangjun WEN Kai CHEN Guangwei DENG Yongjun HUANG School of Information and Communication Engineering Sichuan Provincial Engineering Research Center of Communication Technology for Intelligent IoTUniversity of Electronic Science and Technology of ChinaChengdu 611731China School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 611731China Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of ChinaChengdu 610054China

Micro-gyroscopes using micro-electro-mechanical system(MEMS)and micro-optoelectro-mechanical system(MOEMS)are the new-generation and recently well-developed gyroscopes produced by the combinations of the traditional gyroscope technology and MEMS/MOEMS *** to the working principle and used materials,the newly-reported micro-gyroscopes in recent years include the silicon-based micromechanical vibratory gyroscope,hemispherical resonant gyroscope,piezoelectric vibratory gyroscope,suspended rotor gyroscope,microfluidic gyroscope,optical gyroscope,and atomic *** to different sensitive structures,the silicon-based micromechanical vibratory gyroscope can also be divided into double frame type,tuning fork type,vibrating ring type,and nested ring *** those micro-gyroscopes,in recent years,many emerging techniques are proposed and developed to enhance different aspects of performances,such as the sensitivity,angle random walk(ARW),bias instability(BI),and ***,this paper will firstly review the main performances and applications of those newly-developed MEMS/MOEMS gyroscopes,then comprehensively summarize and analyze the latest research progress of the micro-gyroscopes mentioned above,and finally discuss the future development trends of MEMS/MOEMS gyroscopes.

关键词： Micro-gyroscope MEMS MOEMS angular random walk bias instability

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Collaboratively enhancing electrochemical properties of LiNi_(0.83)Co_(0.11)Mn_(0.06)O_(2) through doping and coating of quadrivalent elements

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Rare Metals 2023年第12期42卷 4103-4114页

作者： Zhao-Zhe Yu Gui-Quan Zhao Fang-Li Ji Hao Tong Qi-Lin Tong Hua-Cheng Li Yan Cheng Guangxi Key Laboratory of Manufacturing Systems and Advanced Manufacturing Technology Guilin University of Electronic TechnologyGuilin 541004China Engineering Research Center of Electronic Information Materials and Devices Ministry of EducationGuilin University of Electronic TechnologyGuilin 541004China Guangxi CNGR New Energy Science&Technology Co. Ltd.Qinzhou 535000China

Ni-rich layered oxides(Ni>80%)with high energy density have become a mainstream cathode material for Li-ion ***,irreversible phase transitions and interface instability are deep-seated challenges in commercializing Ni-rich *** study used a collaborative modification strategy involving doping and coating with quadrivalent elements to construct Ni-rich *** particular,introducing tetravalent Zr makes the valence change of Ni(2+to 4+)more accessible to complete spontaneously during the charging and discharging processes,which significantly suppresses the cationic mixing and irreversible phase transition(H2?H3).Combining the strategy of constructing CeO_(2) coatings on the surface and interfacial spinel-like phases improves the Li+diffusion kinetics and interfacial ***,part of the strongly oxidizing four-valence Ce^(4+)diffuses to the surface layer,further increasing the average valence state of ***,LiNi_(0.83)Co_(0.11)Mn_(0.06)O_(2)(NCM)-Zr@Ce achieves 78.5%outstanding retention at1.0C after 200 cycles within 3.0-4.3 V compared to unmodified NCM with 41.4%*** improved cyclic stability can be attributed to the collaborative modification strategy of the quadrivalent elements,which provides an effective synergistic modification strategy for developing high-performance Li-ion battery cathode materials.

关键词： Collaborative modification strategy Quadrivalent elements Phase transitions Structural degradation Ni-rich layered oxides

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LOEN:Lensless opto-electronic neural network empowered machine vision

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Light(Science & Applications) 2022年第6期11卷 1118-1129页

作者： Wanxin Shi Zheng Huang Honghao Huang Chengyang Hu Minghua Chen Sigang Yang Hongwei Chen Beijing National Research Center for Information Science and Technology(BNRist) Department of Electronic EngineeringTsinghua UniversityBeijing 100084China

Machine vision faces bottlenecks in computing power consumption and large amounts of *** opto-electronic hybrid neural networks can provide assistance,they usually have complex structures and are highly dependent on a coherent light source;therefore,they are not suitable for natural lighting environment *** this paper,we propose a novel lensless opto-electronic neural network architecture for machine vision *** architecture optimizes a passive optical mask by means of a task-oriented neural network design,performs the optical convolution calculation operation using the lensless architecture,and reduces the device size and amount of calculation *** demonstrate the performance of handwritten digit classification tasks with a multiple-kernel mask in which accuracies of as much as 97.21%were ***,we optimize a large-kernel mask to perform optical encryption for privacy-protecting face recognition,thereby obtaining the same recognition accuracy performance as no-encryption *** with the random MLS pattern,the recognition accuracy is improved by more than 6%.

关键词： neural network electronic

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Discriminative low-rank embedding with manifold constraint for image feature extraction and classification

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Optoelectronics Letters 2024年第5期20卷 299-306页

作者： YAN Chunman WEI Shuhong School of Physics and Electronic Engineering Northwest Normal UniversityLanzhou 730070China Engineering Research Center of Gansu Province for Intelligent Information Technology and Application Lanzhou 730070China

The robustness against noise, outliers, and corruption is a crucial issue in image feature extraction. To address this concern, this paper proposes a discriminative low-rank embedding image feature extraction algorithm. Firstly, to enhance the discriminative power of the extracted features, a discriminative term is introduced using label information, obtaining global discriminative information and learning an optimal projection matrix for data dimensionality reduction. Secondly, manifold constraints are incorporated, unifying low-rank embedding and manifold constraints into a single framework to capture the geometric structure of local manifolds while considering both local and global information. Finally, test samples are projected into a lower-dimensional space for classification. Experimental results demonstrate that the proposed method achieves classification accuracies of 95.62%, 95.22%, 86.38%, and 86.54% on the ORL, CMUPIE, AR, and COIL20 datasets, respectively, outperforming dimensionality reduction-based image feature extraction algorithms.

关键词： manifold embedding dimensionality

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A circuit area optimization of MK-3 S-box

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Cybersecurity 2025年第1期8卷 61-71页

作者： Yanjun Li Weiguo Zhang Yiping Lin Jian Zou Jian Liu Information Industry Information Security Evaluation Center The 15th Research Institute of China Electronic Technology Group CorporationBeijing 100083China Henan Key Laboratory of Network Cryptography Technology Zhengzhou 450001China Beijing Electronic Science and Technology Institute No.7 Fufeng RoadFengtai DistricBeijing 100083China College of Computer and Data Science Fuzhou UniversityFuzhou 350108China

In MILCOM 2015,Kelly et *** the authentication encryption algorithm MK-3,which applied the 16-bit *** paper aims to implement the 16-bit S-box with less circuit ***,we classifed the irreducible polynomials over F_(2n)into three *** we compared the logic gates required for multiplication over the fnite feld constructed by the three types of irreducible *** to the comparison result,we constructed the composite felds, F_((2^(4))^(2))and F_((2^(8))^(2)).Based on the isomorphism of fnite felds,the operations over F_(2)^(16)can be conducted over F_((2^(8))^(2)).Similarly,elements over F28 can be mapped to the corresponding elements over F_((2^(4)))^(2).Next,the SAT solver was used to optimize the operations over smaller feld F_(2)^(4).At last,the architecture of the optimized MK-3 S-box was worked *** with the implementation proposed by the original designer,the circuit area of the MK-3 S-box in this paper is reduced by at least 55.9%.

关键词： irreducible operations optimization

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