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Annotation and Retrieval of Retinal Images using Support Vector Machine with Active Learning

Annotation and Retrieval of Retinal Images using Support Vec...

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2019 IEEE international conference on Intelligent Techniques in control, Optimization and Signal Processing, INCOS 2019

作者： Hephzi Punithavathi, I.S. Ganeshkumar, P. Duraipand, P. Shadan College of Engg. Tech Department of Computer Science Engineering Hyderabad India Anna University Regional Campus Department of Information Technology Coimbatore India J.B.Institute of Engg. Technology Department of Electrical Electronics Engineering Hyderabad India

ISBN: (纸本)9781538695425

in the medical field, many images are acquired using different modalities like X-ray, Computed Tomography and Magnetic Resonance Imaging. Organizing these images and retrieving them is a critical task. in this paper, a novel retinal image retrieval and automatic annotation of ten different retinal diseases is presented and is comprised of three steps namely, feature extraction, automatic annotation and retrieval of similar images. in feature extraction, visual features like texture, color and shape were derived from the images and stored in a database. The retinal images are affected by various diseases and have to be identified easily and quickly for better treatment. For automatic annotation, we have considered ten different retinal diseases and annotated the retinal image with its corresponding disease using Support Vector Machine (SVM) with Active Learning (AL) and discriminative based automatic image annotation. in retrieval of images, Bray Curtis distance measure was used to retrieve the similar images by comparing the feature values of images stored in the database. Our proposed system has achieved a precision of 82% and specificity of 96.3%. © 2019 IEEE.

关键词： Support vector machines

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Design of goods transport control system based on PLC

Design of goods transport control system based on PLC

引用

2nd international conference on Computer-Aided Design, Manufacturing, Modeling and Simulation, CDMMS 2012

作者： Yulin, Dong Hehui, Lan College of Electrical Engineering Liao Ning University of Technology LiaoNing China

ISBN: (纸本)9783037855409

This paper introduces realization of the system based on Siemens PLC and IFIX configuration software. The system uses Siemens s7-300 PLC as the control center, and realizes inter-connection with Industrial Switches, control of the belt transport system, and automatic commodity information collection. It is proved that the system could carry out goods safely and stably. Moreover, it is effective to save the manpower and improve the efficiency. © (2013) Trans Tech Publications, Switzerland.

关键词： control systems

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PMDC motor speed control with fuzzy logic algorithm using PIC16F877 micro controller and plotting data on monitor

PMDC motor speed control with fuzzy logic algorithm using PI...

引用

5th international conference on Soft computing, computing with Words and Perceptions in System Analysis, Decision and control, ICSCCW 2009

作者： Işik, Ahmet Karakaya, Oktay Öner, P. Alper Eker, Mehmet Kubilay Balikesir University Graduate School of Natural and Applied Science Balikesir Turkey Balikesir University Electrical and Electronics Engineering Balikesir Turkey

ISBN: (纸本)9781424434282

In this study, speed of permanent magnet dc (PMDC) motor is controlled with Fuzzy Logic (FL) algorithm at real time. For real time closed loop control, it has been used a PIC16F877 micro controller usage with 8 bit resolution. Only 3 membership functions which are called Negative (N), Zero (Z) and Positive (P) are used definition for FL algorithm, because of the difficulty to write the software to the micro controller via compiler program. Membership degrees of the functions are defined from 0 to 255 which is 8 bit unsigned maximum value. Integer numbers are used for programming algorithm, because compiler program using to write the software program to the micro controller is not enough sensitive for floating point number. Instantaneous values of the speed of the motor are transferred to PC with another PIC16F877 micro controller and plotting on monitor using interface program developed from DELPHI. ©2009 IEEE.

关键词： controllers

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Deep Learning-Based Object Detection System for Crowd Monitoring in High-Security Areas 2

Deep Learning-Based Object Detection System for Crowd Monito...

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2nd IEEE international conference on Intelligent and Innovative Technologies in computing, electrical and Electronics, ICIITCEE 2024

作者： Pandey, Anurag Kandpal, Hitesh Rawat, Shubham Singh Vaidya, Himadri Rawat, Ruchira Kumar, Bura Vijay Computer Science and Engineering Graphic Era Hill University Dehradun India Computer Science and Engineering Graphic Era Deemed to Be University Dehradun India School of Computer Science and Artificial Intelligence Sr University Warangal India

ISBN: (纸本)9798350306415

In order to maintain crowd control and assure safety, contemporary security systems require effective monitoring tools for sensitive and high-traffic locations. In particular, headcount estimate in sensitive areas like high-security buildings, crowded areas is the subject of this research's novel using deep learning algorithms for real-time object identification in surveillance settings. The main goal is to create a reliable system that can count the number of people in a certain area, recognize their presence, and sound an alarm when the number of people in the crowd rises over pre-established levels. YOLO (You Only Look Once), RetinaNet, SSD (Single Shot MultiBox Detector), and RCNN (Region-based Convolutional Neural Networks) are four of the cutting-edge deep learning models that are applied in this study of object recognition. In order to identify the best method for precise and effective headcount estimation, the study comprises a comparison review of various models. And of all the models examined, YOLO consistently showed the greatest results for precision, recall, and average precision, making it the most efficient model for this specific project. © 2024 IEEE.

关键词： Deep learning algorithms Object detection RCNN RetinaNet SSD YOLO

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2020 2nd international conference on Artificial Intelligence Technologies and Application, ICAITA 2020

2020 2nd International Conference on Artificial Intelligence...

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2020 2nd international conference on Artificial Intelligence Technologies and Application, ICAITA 2020

The proceedings contain 196 papers. The topics discussed include: exploration of cloud computing resource pool virtualization technology and implementation methods;evaluation of interior design schemes based on artificial intelligence processing technology;research on the reform of accounting teaching mode under the impact of artificial intelligence;indoor parking method based on cooperation of intelligent vehicle and parking lot;research on network security vulnerability detection method based on artificial intelligence;innovative research on the teaching mode of piano group lessons in higher vocational preschool education based on AI;research on the practice of talent cultivation based on the improvement of innovation ability —— taking electrical engineering automation technology as an example;optimization strategy of computer automatic control system based on artificial intelligence;intelligent control of threshing and cleaning system based on big data;social insurance management depends on the development of computer information technology;and deep matrix factorization based on self-attention mechanism for student grade prediction.

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Performance Analysis of Electric Vehicle using BLDC Motor Drive 7

Performance Analysis of Electric Vehicle using BLDC Motor Dr...

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7th international conference on Intelligent computing and control Systems, ICICCS 2023

作者： Vijayaraja, L. Dhanasekar, R. Harini, K. Hemapriya, T. Subhasri, S. Kesavan, Rupa Sri Sairam Institute of Technology Department of Electrical and Electronics Engineering Chennai India Sri Venkateswara College of Engineering Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350397253

A study on position and speed is made on BLDC (Brushless DC motor) in this research. The study is performed based on the sensor less technology which includes background investigation. Compared to the conventional method, the reliability and the performance of BLDC motor is improved using the proposed design. In the simulation, controlling the speed of BLDC motor is performed. In simulation, the speed of the BLDC motor remains constant even when the voltage varies. Further in the real time experimentation sensor less are studied in terms of merits and demerits, further an analysis is made on design parameter, issue in implementation and the application. The study includes an Electro Motive Force sensing methods, Terminal Voltage Sensing and Terminal Current Sensing. Using microcontroller (Atmega8A) board and Electronic Speed controller, the speed of the motor is controlled by varying the 10k potentiometer. The parameter like speed and rpm are obtained and shown in the load display. © 2023 IEEE.

关键词： Brushless DC motors

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The design and finite element analysis of a compliant 3-DOF spatial translational ultra-precise positioning platform

The design and finite element analysis of a compliant 3-DOF ...

引用

IEEE international conference on Intelligent computing and Intelligent Systems (ICIS)

作者： Chen, Qiang Huang, Yong Zhu, Dachang Zhou, Mugui College of Mechanical and Electrical Control Engineering Jiangxi University of Science and Technology Ganzhou China

ISBN: (纸本)9781424465835

Ultra-precise positioning platform plays a significant role in ultra-precise operation and micro-operation. A new compliant 3-DOF spatial translational ultra-precise positioning platform is proposed and it overcomes the shortcomings of the general conventional drive and transmission such as low speed of response and low displacement resolution. The platform is consist of flexible hinges which provide elastic supporting, and with piezoelectric actuators as its drives which has high stiffness, high speed of dynamic response, high kinematic accuracy and high resolution. The end effector of the platform come to spatial ultra-precise positioning after it drived by the compliant parallel links which drived by piezoelectric actuators. The finite element analysis shows it can reach to positioning accuracy in nanoscale. ©2010 IEEE.

关键词： Finite element method

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Speech Disorders Analysis Using a Line of Narrow-Band Filters 6

Speech Disorders Analysis Using a Line of Narrow-Band Filter...

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6th international Youth conference on Radio Electronics, electrical and Power engineering, REEPE 2024

作者： Belodedov, Mikhail V. Fonkants, Roman V. Bauman Moscow State Technical University Automatic Information Processing and Control Systems Moscow Russia

ISBN: (纸本)9798350382891

The paper examines applicability of a line of the narrow-band filters in analyzing the speech disorders. It describes a method for processing the speech signals using a line of the narrow-band filters and provides mathematical description of the complex-valued first-order filter that could be introduced as the narrow-band filter. Experiment results showed that based on the set of responses obtained using the proposed line of the narrow-band filters it becomes possible to determine whether speech disorders are present in the original speech recording. Analyzing the work results made it possible to conclude that the filter responses could be successfully used as the input data in various modules identifying and classifying the speech disorders. © 2024 IEEE.

关键词： Audio signal processing

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Energy Efficient 2D-DOA Based Precoding Approach for 5G Multicell Massive MIMO System 3

Energy Efficient 2D-DOA Based Precoding Approach for 5G Mult...

引用

3rd IEEE international Maghreb Meeting of the conference on sciences and Techniques of automatic control and Computer engineering, MI-STA 2023

作者： Ali, Ehab Shglouf, Ibrahim Balfaqih, Mohammed Alzughid, Saleh Mustafa, Haytham Saied, Muftah University of Benghazi Benghazi Libya Libyan International University Benghazi Libya University of Jeddah Jeddah Saudi Arabia College of Science and Technology Qaminis Libya College of Electrical & Electronics Technology Benghazi Libya National Center for Quality Assurance and Accrediation Benghazi Libya

ISBN: (纸本)9798350319897

This article presents an efficient downlink zeroforcing (ZF) precoding technique that utilizes the twoDimensional Direction of Arrival (2D-DOA) beam-spaced method to maximize the energy efficiency of multi-cell massive- MIMO systems. The approach for estimating the critical elevation and azimuth angles of detected signals from distributed sources in multi-cell massive-MIMO systems is also detailed. A mathematical model for energy efficiency of downlink ZF precoding is developed using these critical angles, and its performance is evaluated and compared to conventional 2D-DOA methods. Simulation results demonstrate that the proposed method significantly improves energy efficiency with a gain of approximately 98.3% compared to the deterministic ZF precoding method. © 2023 IEEE.

关键词： MIMO systems

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Deep Learning Used to Detect Gear Inspection 24

Deep Learning Used to Detect Gear Inspection

引用

24th IEEE/ACIS international Winter conference on Software engineering, Artificial Intelligence, Networking and Parallel/Distributed computing, SNPD 2022

作者： Jian, Jia-Xian Wang, Chuin-Mu National Cheng Kung University Department of Electrical Engineering Tainan Taiwan National Chin Yi University of Technology Department of Computer Science and Information Engineering Taichung Taiping Taiwan

ISBN: (纸本)9798350310412

automatic gear defect detection equipment is relatively expensive, so small and medium-sized enterprises cannot afford the cost of such equipment. Therefore, most companies still use manual inspection methods for gear defect detection. Manual inspection methods not only take a long time but also has uneven detection quality. This paper proposes to use AI technology to build a cheap and fast gear defect detection method. And this method is used to complete the detection of gear tooth profile defects, tooth pitch defects and central hole defects. The method proposed in this paper is divided into four steps. In the first step, the ResNet model [1] is used to classify whether the gear image is complete or not. In the second step, the YOLOv4 model [2] is used to find the rectangular area of the tooth shape and tooth pitch in the image and cut it out. The third step is to use the UNet model [3] to segment the tooth profile and pitch profile, and calculate the area occupied by the profile. Finally, whether the difference from the average area is too large is used as the basis for judging whether the gear is defective. In the experiment result, 186 gear images are used for detection, and the obtained accuracy is about 91%. This result in addition to verifying the feasibility of the proposed method, it is also found that the proposed method can quickly and accurately detect gear defects that are difficult to judge by human eyes. © 2022 IEEE.

关键词： Defects

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