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Time and Space Efficient Multi-Model Convolution Vision Transformer for Tomato Disease Detection from Leaf Images with Varied Backgrounds

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computers, Materials & Continua 2024年第4期79卷 117-142页

作者： Ankita Gangwar Vijaypal Singh Dhaka Geeta Rani Shrey Khandelwal Ester Zumpano Eugenio Vocaturo Department of Computer and Communication Engineering Manipal University JaipurJaipurIndia Department of IoT and Intelligent Systems Manipal University JaipurJaipurIndia Department of Computer Engineering ModellingElectronics and Systems(DIMES)University of CalabriaRende(Cosenza)Italy National Research Council Institute of Nanotechnology(NANOTEC)Rende(Cosenza)Italy

A consumption of 46.9 million tons of processed tomatoes was reported in 2022 which is merely 20%of the total *** increase of 3.3%in consumption is predicted from 2024 to *** are also rich in iron,potassium,antioxidant lycopene,vitamins A,C and K which are important for preventing cancer,and maintaining blood pressure and glucose ***,tomatoes are globally important due to their widespread usage and nutritional *** face the high demand for tomatoes,it is mandatory to investigate the causes of crop loss and minimize *** are one of the major causes that adversely affect crop yield and degrade the quality of the tomato *** leads to financial losses and affects the livelihood of ***,automatic disease detection at any stage of the tomato plant is a critical *** learning models introduced in the literature show promising results,but the models are difficult to implement on handheld devices such as mobile phones due to high computational costs and a large number of ***,most of the models proposed so far work efficiently for images with plain backgrounds where a clear demarcation exists between the background and leaf ***,the existing techniques lack in recognizing multiple diseases on the same *** address these concerns,we introduce a customized deep learning-based convolution vision transformer *** achieves an accuracy of 93.51%for classifying tomato leaf images with plain as well as complex backgrounds into 13 *** requires a space storage of merely 5.8 MB which is 98.93%,98.33%,and 92.64%less than stateof-the-art visual geometry group,vision transformers,and convolution vision transformermodels,*** training time of 44 min is 51.12%,74.12%,and 57.7%lower than the above-mentioned ***,it can be deployed on(Internet of Things)IoT-enabled devices,drones,or mobile devices to assist farmers in the real-time monitoring of tomato *** p

关键词： Tomato disease transformer deep learning mobile devices

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Low-power test pattern generator using modified LFSR

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Aerospace Systems 2024年第1期7卷 67-74页

作者： Govindaraj, V. Dhanasekar, S. Martinsagayam, K. Pandey, Digvijay Pandey, Binay Kumar Nassa, Vinay Kumar Department of Electronics and Communication Engineering Dr NGP Institute of Technology Coimbatore641048 India Department of Electronics and Communication Engineering Sri Eshwar College of Engineering Coimbatore641202 India Department of Electronics and Communication Engineering Karunya Institute of Technology and Sciences Coimbatore641114 India Department of Technical Education Uttar Pradesh Kanpur India Department of Information Technology College of Technology Govind Ballabh Pant University of Agriculture and Technology Pantnagar Udham Singh Nagar Uttarakhand India Computer Science Engineering Department Rajarambapu Institute of Technology Rajaramnagar Sakharale Tel Walwa Dist Sangli Maharashtra Islampur415414 India

Low-power designs are getting increased significance in numerous applications like high-performance computing and wireless communication due to the rise in power dissipation. Power dissipation of VLSI (very large scale integration) circuits in test mode is much higher than in the normal operation mode due to the high frequency of applied test patterns. Product lifetime, yield, reduced performance, and circuit damage will result from this additional power consumption in testing. Therefore, the main objective of today’s test applications is to minimize power dissipation by increasing the correlation of applied successive test vectors. Low-power test pattern generator (TPG) using LFSR (linear feedback shift register) and binary to the excess-4 converter and binary ripple counter is proposed. The test vectors generated by the TPG have a high correlation between successive test vectors, which leads to minimum switching. During the testing of benchmark circuits, the proposed method shows a significant reduction in dynamic power consumption concerning its peer works. © Shanghai Jiao Tong University 2023.

关键词： Electric power utilization

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Real-time programmable metasurface for terahertz multifunctional wave front engineering

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Light(Science & Applications) 2023年第9期12卷 1795-1806页

作者： Feng Lan Luyang Wang Hongxin Zeng Shixiong Liang Tianyang Song Wenxin Liu Pinaki Mazumder Ziqiang Yang Yaxin Zhang Daniel M.Mittleman Sichuan THz Communication Technology Engineering Research Center School of Electronic Science and EngineeringUniversity of Electronic Science and Technology of ChinaChengdu 611731China Yangtze Delta Region Institute(Huzhou) University of Electronic Science and Technology of ChinaHuzhou 313000China Zhangjiang Laboratory Shanghai 201204China National Key Laboratory of Solid-State Microwave Devices and Circuits Hebei Semiconductor Research InstituteShijiazhuang 050051China Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100094China University of Chinese Academy of Sciences School of ElectronicElectrical and Communication EngineeringBeijing 101408China Department of Electrical Engineering and Computer Science University of MichiganAnn ArborMI 48109USA School of Engineering Brown UniversityProvidenceRI 02912USA

Terahertz(THz)technologies have become a focus of research in recent years due to their prominent role in envisioned future communication and sensing *** of the key challenges facing the field is the need for tools to enable agile engineering of THz wave ***,we describe a reconfigurable metasurface based on GaN technology with an array-of-subarrays *** subwavelength-spaced array,under the control of a 1-bit digital coding sequence,can switch between an enormous range of possible configurations,providing facile access to nearly arbitrary wave front control for signals near 0.34 *** demonstrate wide-angle beam scanning with 1°of angular precision over 70 GHz of bandwidth,as well as the generation of multi-beam and diffuse wave fronts,with a switching speed up to 100 *** device,offering the ability to rapidly reconfigure a propagating wave front for beam-forming or diffusively scattered wide-angle coverage of a scene,will open new realms of possibilities in sensing,imaging,and networking.

关键词： wave scattered arbitrary

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A Hybrid Approach for Diagnosing Diabetic Retinopathy in Retinal Fundus Images using an Adaptive Canny Edge Detection approach 15

A Hybrid Approach for Diagnosing Diabetic Retinopathy in Ret...

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15th International Conference on Computing communication and Networking Technologies, ICCCNT 2024

作者： Manjula Devi, R. Kowsalya, M. Dinesh, P.M. Ponmurugan, P. Berlin, A. Kavin Kumar, K. Sangeetha, M. Chandrasekaran, Gokul Department of Computer Science and Engineering KPR Institute of Engineering and Technology Coimbatore India Department of Computer Science and Engineering Erode Sengunthar Engineering College Thuduppathi638057 India Department of Electronics and Communication Engineering Sona College of Technology Salem636005 India Chennai600078 India Department of Electronics and Communication Engineering Jansons Institute of Technology Coimbatore India Department of Electronics and Communication Engineering Kongu Engineering College Perundurai638060 India Department of Information Technology Dr.N.G.P. Institute of Technology Tamilnadu Coimbatore India Department of Electronics and Communication Engineering Karpagam Institute of Technology Coimbatore India

ISBN: (纸本)9798350370249

Individuals diagnosed with diabetes are susceptible to developing diabetic retinopathy (DR), a degenerative eye condition that affects the retina. When blood vessels in the retina get damaged, it can cause permanent vision impairment or even blindness if the underlying condition is not addressed quickly enough. Early diagnosis and treatment of this disease can save a patient's eyesight and prevent blindness. Successful medications for DR are available, but people with diabetes need to be identified and monitored early on. In order to diagnose diabetic retinopathy, many physical examinations have to be conducted;however, these types of exams require more time to complete. Adaptive Canny Edge Detection Training using Adaptive Skipping technique (ACEDIAS) is used in this research to speed up the detection process of diabetic retinopathy by detecting the edge and boost diagnostic accuracy. The study team chooses to use a 2063-image dataset compressed from Kaggle's library. The suggested ACEDIAS model is evaluated for its performance using the measures such as accuracy, recall, precision, and F1-score. It has been demonstrated through simulation that the suggested ACEDIAS model outperforms the existing models. ©2024 IEEE.

关键词： Ophthalmology

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Wireless Gesture-Driven Navigation for Autonomous Robots: An Innovative Human-Machine Interface Approach

Wireless Gesture-Driven Navigation for Autonomous Robots: An...

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2024 International Conference on System, Computation, Automation and Networking, ICSCAN 2024

作者： Zarina Begum, M. Gowthami, V. Ramya, M. Vijaya Shanthi, V. Manakula Vinayagar Institute of Technology Department of Electronics and Communication Engineering Puducherry India Christ Institute of Technology Department of Computer Science Engineering Puducherry India

ISBN: (数字)9798331510022

ISBN: (纸本)9798331510022

As more and more features are added to the car's Human- Machine Interface (HMI), device management becomes increasingly difficult. Making the most of the many human senses is consequently a tactic to facilitate using in-car technologies. With the use of an Arduino Uno and this concept, a car robot with wireless navigation can be built. The robot chassis's direction is altered in accordance with the statement specified in the Arduino code, which is run when the position of the hand is monitored and the designed coordinates are taken into consideration as the parameter. in order for it to carry out the necessary actions, such as going ahead, backward, turning left, turning right, and stopping. © 2024 IEEE.

关键词： DC motors

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Distribution Decomposition and Sum-Capacity Results of Two-User Optical Intensity Multiple Access Channels

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IEEE Transactions on Information Theory 2023年第9期69卷 5532-5549页

作者： Li, Longguang Chen, Ru-Han Zhou, Jing East China Normal University Department of Communication and Electronic Engineering Shanghai200062 China Sixty-Third Research Institute National University of Defense Technology Nanjing210044 China Shaoxing University Department of Computer Science and Engineering Shaoxing312010 China

This paper investigates the sum-capacity of two-user optical intensity multiple access channels with per-user peak- or/and average-intensity constraints. By leveraging tools from the decomposition of certain distributions, we derive several lower bounds on the sum-capacity. In the high signal-to-noise ratio (SNR) regime, some bounds asymptotically match or approach the sum-capacity, thus closing or reducing the existing gaps to the high-SNR asymptotic sum-capacity. At moderate SNR, some bounds are also fairly close to the sum-capacity. © 1963-2012 IEEE.

关键词： Gaussian noise (electronic)

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A Two-Phase Multi-Class Botnet Labeling Approach for Real-World Traffic 6

A Two-Phase Multi-Class Botnet Labeling Approach for Real-Wo...

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6th International Conference on Artificial Intelligence in Information and communication, ICAIIC 2024

作者： Lo, Ta-Chun Yang, Shan-Hong Chang, Jyh-Biau Chen, Chung-Ho Shieh, Ce-Kuen National Cheng Kung University Department of Electrical Engineering Tainan Taiwan Institute of Computer and Communication Engineering National Cheng Kung University Tainan Taiwan Lunghwa University of Science and Technology Department of Electronic Engineering Taoyuan Taiwan

ISBN: (纸本)9798350344349

Within the realm of cybersecurity, botnets represent an increasingly formidable threat, characterized by diverse types exhibiting distinct behavioral patterns and characteristics. This study addresses the imperative need for real-time botnet activity detection by introducing a multi-class labeling system tailored for real-world network traffic. Employing clustering algorithms and a semi-supervised learning framework, this system efficiently labels benign traffic and performs multi-class labeling for various botnet traffic categories. Hierarchical Density-based Spatial Clustering of Applications with Noise (HDBSCAN) is harnessed for clustering both synthetic and real-world datasets, significantly enhancing labeling coverage. The remaining traffic is designated as 'unknown' and subjected to identification through a semi-supervised learning approach. A comparative analysis underscores the superiority of HDBSCAN over Density-based Spatial Clustering of Applications with Noise (DBSCAN), successfully clustering an additional 11% of data. Remarkably, our system exhibits substantial advancements in data labeling when juxtaposed with prior research efforts. This research introduces an effective solution for botnet labeling in the context of network security, thereby enhancing the capacity for detecting and mitigating malicious botnet activities. © 2024 IEEE.

关键词： Clustering algorithms

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DESIGN OF RF FEEDING NETWORK [1:8] USING UNEQUAL AMPLITUDE HYBRID COUPLER FOR LOW SLL X-BAND RADAR APPLICATIONS

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Telecommunications and Radio engineering (English translation of Elektrosvyaz and Radiotekhnika) 2025年第5期84卷 1-19页

作者： Kothapudi, Venkata Kishore Sunayana, Lella Divya, Shaik Kumar, Vijay Pappula, Lakshman Gottapu, Srinivasa Kiran Guntur District Andhra Pradesh Vadlamudi522213 India Department of Communication Engineering School of Electronics Engineering Vellore Institute of Technology Tamil Nadu Vellore632014 India Department of Electrical Electronics and Communication Engineering GITAM School of Technology GITAM University Andhra Pradesh Visakhapatnam530045 India School of Science and Engineering Engineering and Computer Science Department Benedict College 1600 Harden St. ColumbiaSC29204 United States

The design simulation and manufacturing of an x-band frequency uneven amplitude 90° hybrid coupler are described in this paper. This hybrid coupler is used to create a feeder network with eight output ports operating at 9.3 GHz. The overall goal is to design and analyze an uneven power feeding network (1:8) for low SLL x-band radar applications employing a hybrid coupler. The specific goal is to create a hybrid coupler with equal amplitude, a hybrid coupler with uneven amplitude [Taylor’s amplitude = –17 dB], and a feeding network using hybrid couplers. The goal of this research is to improve the ability of a single transmitter to provide power to more than one antenna, all at a time either equally or unequally, and this can be achieved by designing a desired number of hybrid couplers and connecting them to the specific number of antennas at the output end and to the single transmitter at the input end. © 2025 by Begell House, Inc.

关键词： Transmitters

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A deep Q-learning model for sequential task offloading in edge AI systems

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Intelligent and Converged Networks 2024年第3期5卷 207-221页

作者： Dong Liu Shiheng Gu Xinyu Fan Xu Zheng Department of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu 610000China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of ChinaShenzhen 515100China Department of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu 610000China

Currently,edge Artificial Intelligence(AI)systems have significantly facilitated the functionalities of intelligent devices such as smartphones and smart cars,and supported diverse applications and *** fundamental supports come from continuous data analysis and computation over these *** the resource constraints of terminal devices,multi-layer edge artificial intelligence systems improve the overall computing power of the system by scheduling computing tasks to edge and cloud servers for *** efforts tend to ignore the nature of strong pipelined characteristics of processing tasks in edge AI systems,such as the encryption,decryption and consensus algorithm supporting the implementation of Blockchain ***,this paper proposes a new pipelined task scheduling algorithm(referred to as PTS-RDQN),which utilizes the system representation ability of deep reinforcement learning and integrates multiple dimensional information to achieve global task ***,a co-optimization strategy based on Rainbow Deep Q-Learning(RainbowDQN)is proposed to allocate computation tasks for mobile devices,edge and cloud servers,which is able to comprehensively consider the balance of task turnaround time,link quality,and other factors,thus effectively improving system performance and user *** addition,a task scheduling strategy based on PTS-RDQN is proposed,which is capable of realizing dynamic task allocation according to device *** results based on many simulation experiments show that the proposed method can effectively improve the resource utilization,and provide an effective task scheduling strategy for the edge computing system with cloud-edge-end architecture.

关键词： edge computing task scheduling reinforcement learning Rainbow Deep Q-Learning(RainbowDQN)

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Early Detection of Autism Spectrum Disorder (ASD)-A Deep Learning Approach 1st

Early Detection of Autism Spectrum Disorder (ASD)-A Deep Lea...

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1st International Conference on Intelligent Computing, Smart communication, and Network Technologies, ICICSCNT 2023

作者： Nirmalapriya, G. Ravikumar, K. Jayasri, M. PrasannaKumar, V. Department of ECE Rajalakshmi Institute of Technology Chennai India Department of Computer and Communication Engineering Rajalakshmi Institute of Technology Chennai India Computer Science Engineering Rajalakshmi Institute of Technology Chennai India

ISBN: (纸本)9783031759567

In this research, we put together a deep learning strategy that brings together the medical biomarker data from EEG tests and information from both clinical observations and inquiries to recognize the children with a Autism Spectrum Disorder (ASD). We expect that it can improve the effectiveness of identification significantly in addition to minimizing the expenditure. To begin with, our approach employed a pioneering tactic for selecting a neuronal signal landmarks derived from an eye movement, facial expression, and EEG results. This research showed that using a combination of Local Binary Pattern algorithm and deep learning classification led to a 87.50% accurate classification rate for multi-modal data merging. Finding a point to this method of detection as highly useful and effective for diagnosing ASD in young children. Graphs and confusion matrices unveiled different discrimination methods of EEG, personal behavior, and questionaries’ for discrepancy discrimination between ASD individuals and typically developing kids, with EEG being the most useful in drawing distinctions. Studies portray the physiological and behavioral important complementary characteristics. The combination of complementary information in this study proposed the deep learning approach has led to a significant improvement in classification accuracy. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Diseases

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