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检索条件"任意字段=International Conference on Electrical Engineering Computing Science and Automatic Control"

共 15478 条记录，以下是61-70 订阅

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Exploring the Use of Transfer Learning for Automated Brain Tumor Segmentation 5th

Exploring the Use of Transfer Learning for Automated Brain T...

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5th international conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： Savita Jaison, Feon Nautiyal, Kshitij Sunitha, B.J. Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bengaluru India Department of Electrical Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India

ISBN: (纸本)9789819780426

Switch getting to know has become increasingly famous in many aspects of pc vision, including picture segmentation. This paper explores switch-gaining knowledge for automated brain tumor segmentation using a deep getting-to-know structure known as U-net. U-internet is a convolution neural community version that has been used efficiently to ramify scientific image segmentation obligations in the beyond. This work utilizes a U-internet model skilled on a huge-scale brain tumor segmentation dataset. The version plays nicely at the utility of brain tumor segmentation, achieving an average cube coefficient of zero. Ninety-three on check scans. Moreover, qualitative consequences display that the U-net version produces segmentation masks with few false-nice mistakes. These consequences reveal the capability of switch getting to know for automatic mind tumor segmentation. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Image segmentation

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Advanced Fire Detection and Extinguishing Rover with YOLOv8

Advanced Fire Detection and Extinguishing Rover with YOLOv8

引用

2025 IEEE international Students' conference on electrical, Electronics and Computer science, SCEECS 2025

作者： Shah, Aaryan Kumar Yadav, Anil Awal, Sanika Kashyap, Deekshit Pinge, Ninad Kaushik, Shreya Vit Bhopal University School of Computing Science Engineering and Artificial Intelligence Madhya Pradesh Sehore India

ISBN: (纸本)9798331529833

The project 'Advanced Fire Detection and Extinguishing Rover utilizing YOLOv8' introduces a cutting-edge, fire-detection and suppression system that uses deep learning and robotic automation to improve safety. The system uses the YOLOv8 object identification model, which was trained on several fire-related datasets, to effectively identify fire dangers in real-time using live video feeds processed using Python and OpenCV. When the system detects a fire with a high confidence score, it labels the impacted regions and sends the rover driven by the remote controlled and Arduino microcontroller. The rover's servo motor independently directs an inbuilt fire extinguisher to extinguish flames. Bluetooth allows remote monitoring and control, ensuring that everything runs smoothly and securely. This combination of artificial intelligence, computer vision, and robotics provides a revolutionary method for proactive fire-risk mitigation that aims to reduce damage, improve safety, and save lives. © 2025 IEEE.

关键词： Fire extinguishers

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Smart Grid Solutions for Sustainable Mining: A Cost-Effective Energy Management Framework with Optimization Algorithms 6

Smart Grid Solutions for Sustainable Mining: A Cost-Effectiv...

引用

6th international conference on Mobile computing and Sustainable Informatics, ICMCSI 2025

作者： Parvathareddy, Sravani Yahya, Abid Amuhaya, Lilian Livutse Samikannu, Ravi Department of Electrical and Communications Systems Engineering Botswana International University of Science and Technology Palapye Botswana Department of EEE New Era Engineering College South East Botswana

ISBN: (纸本)9798331522667

This research work focuses on conceptualizing and modeling smart grid infrastructure. The project's main objective is to develop a smart grid infrastructure to improve energy management in industrial processes. Regenerate has deployed a system that uses renewable energy sources like solar photovoltaic (PV) arrays and wind turbines combined with batteries for energy storage. This research work describes a method that first creates synthetic data and then uses a polynomial function to precisely model the statistical fluctuations inherent in the output of renewable energy sources. The process is carried out using MATLAB. A simulation model created using Simulink is also applied to build a smart grid that includes dynamic load control, demand side management DSM, and various control system configurations. The simulation demonstrates that it is possible to produce electricity with minimal or no depreciation related to an increased dependency on renewable energy sources. It can also function at a higher ratio of energy output produced by traditional sources than previously credited within New Zealand while having substantially fewer overall expenses associated with carbon emissions. © 2025 IEEE.

关键词： Demand side management

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5th international conference on Data science, Machine Learning and Applications, ICDSMLA 2023

5th International Conference on Data Science, Machine Learni...

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5th international conference on Data science, Machine Learning and Applications, ICDSMLA 2023

ISBN: (纸本)9789819780426

The proceedings contain 128 papers. The special focus in this conference is on Data science, Machine Learning and Applications. The topics include: Digitization of Monuments – An Impact on the Tourist Experience with Special Reference to Hampi;resume Parser Using Machine Learning;IOT Based Smart Hydroponics System;comparative Study of Machine Learning and Deep Learning Techniques for Cancer Disease Detection;High Thruput Modulation Approaches Used in Next Generation WiF’s Under Multi-impairments Environments with MATLAB Codes;skin Disease Detection;root Vegetable Crop Recommendation System Based on Soil Properties and Environmental Factors;deep Learning Model Development for an automatic Healthcare Edge computing Application;Empathetic Conversations in Mental Health: Fine-Tuning LLMs for Supportive AI Interactions;exploring Block Chain Technology with Applications, and Future Prospects;a Comprehensive Review of Soft computing Enabled Techniques for IoT Security: State-of-the-Art and Challenges Ahead;Performance Analysis of Machine Learning Algorithms on Imbalanced Datasets Using SMOTE Technique;An AI Based Nutrient Tracking and Analysis System;power Saving Mechanism for Street Lights System Using IoT;automatic Login System Using ATTINY85 IC;forecasting Stock Prices: A Comparative Analysis of Machine Learning, Deep Learning, and Statistical Approaches;smart Vision Bot;robots in Logistics: Apprehension of Current Status and Future Trends in Indian Warehouses;smart Healthcare: Enhancing Patient Well-Being with IoT;Detection of B-ALL Using CNN Model and Deep Learning;a Comprehensive Analysis for Advancements and Challenges in Deep Learning Models for Image Processing;a Comprehensive Survey on Enhancing Patient Care Through Deep Learning and IoT-Enabled Healthcare Innovations;attention-Based Image Caption Generation.

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5th international conference on Data science, Machine Learning and Applications, ICDSMLA 2023

5th International Conference on Data Science, Machine Learni...

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5th international conference on Data science, Machine Learning and Applications, ICDSMLA 2023

ISBN: (纸本)9789819780303

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Design of an airborne electromechanical interface unit with lightweight and extendable functions 5

Design of an airborne electromechanical interface unit with ...

引用

5th international conference on Mechanical engineering and Materials, ICMEM 2024

作者： Jing, Li-Xiong Wang, Peng-Bo Luo, De-Jie School of Computer Science Northwestern Polytechnical University Shaanxi Xi'an710072 China Xi'an Institute of Computing Technology Aviation Industry Shaanxi Xi'an710065 China

ISBN: (数字)9781510688971

ISBN: (纸本)9781510688964

This paper introduces a lightweight, configurable interface, bus can be cascaded expansion of the airborne electromechanical interface unit. The device is applied to the electrical control system of small and medium-sized UAV, which has the advantages of lightweight, low cost, strong versatility and extendable function. In the design of the electromechanical interface unit, the distributed processing idea applied in the large passenger aircraft is used for reference. The main feature is that the device has greater flexibility, can adapt to the interface characteristics of various sensors and actuators, and has the ability of configurable input and output interfaces and extensible bus communication nodes. The software design of the electromechanical interface unit adopts an open architecture, modular and componentized design, and the table driving technology is applied in the design, which can flexibly configure the software functions, quickly realize the function iteration of the software, and has a certain health management ability. © 2025 SPIE.

关键词： Photons

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How Lightweight Deep Learning Enhances Performance in DPU-Accelerated Autonomous Driving on Zynq SoC 11

How Lightweight Deep Learning Enhances Performance in DPU-Ac...

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11th international conference on Mechatronics and Robotics engineering, ICMRE 2025

作者： Hwang, Gyu Hyeon Oh, HoBin Jeon, Jae Wook Sungkyunkwan University Department of Electrical and Computer Engineering Suwon Korea Republic of Sungkyunkwan University Department of Computer Science and Engineering Suwon Korea Republic of

ISBN: (纸本)9798331509293

This study presents a lightweight deep learning model developed for DPU-accelerated systems. It aims to provide real-time autonomous driving on resource-constrained systems such as the Ultra96v2. A customized kids electric car served as the platform. Custom power supply and steering control systems were set up in the car to enable real-world testing. To enhance inference performance, various methods were used. These included input size reduction, channel-pruning, and quantization. As a consequence, the pruned and quantized YOLOv3-Tiny model produced a frame rate of 67.592 FPS. This is roughly a 25x increase over the original YOLOv3's 2.715 FPS on Ultra96v2's PL domain. These results show that real-time deployment is feasible on FPGA-based platforms. The work offers insights for creating efficient and scalable embedded systems for self-driving vehicle system. © 2025 IEEE.

关键词： Direct digital control systems

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Efficient One-Dimensional Current Configuration and Encoding Method for ITSC Diagnosis of Three-Phase Induction Motor Using CNN 11

Efficient One-Dimensional Current Configuration and Encoding...

引用

11th international conference on Mechatronics and Robotics engineering, ICMRE 2025

作者： Goh, Yeong-Jin Kim, Kyoung-Min School of Electrical & Control Engineering Tongmyong Uinv. Busan Korea Republic of Chonnam National Univ. Dept. Electrical & Semiconductor Engineering Yeosu Korea Republic of

ISBN: (纸本)9798331509293

One-dimensional (1D) time series vibrations are typically exposed to irregular noise when applied to actual industrial sites that may reduce the efficiency of supervised learning. While current data may be associated with low-data loss, they may affect the increase in the number of CNN channels. This study proposes a fault diagnosis using current data and an efficient image encoding method for inter-turn short circuit (ITSC) fault diagnosis of a three-phase induction motor using convolutional neural networks (CNN). To address this problem, only the D-axis component of the D-Q synchronous reference frame was used to demonstrate the information loss over time by analyzing whether ITSC occurs during the transformation process (three to single phase). The SWM and GAF methods were compared to investigate an efficient input image construction method that could be applied to CNN by utilizing the 1D D-axis signal. In the configuration of big data, the variation of the total load (no- to full-load state) was considered and applied to CNN. As a result, the GAF and SWM methods respectively yielded accuracies of 74 % and 65%. The learning time (14.74 s) was not significantly different from the overall time but it was shorter for epochs © 2025 IEEE.

关键词： Convolutional neural networks

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Development and Performence Analysis of a tunable LED luminaire 4

Development and Performence Analysis of a tunable LED lumina...

引用

4th international conference on Power, control and computing Technologies, ICPC2T 2025

作者： Pranta, Prasanjit Ghosh Wasif, Shaheen Sahana, Sangita Electrical Engineering Department Jadavpur University Kolkata India School of Illumination Science Engineering and Design Jadavpur University Kolkata India Electrical Engineering Department Jadavpur University Kolkata India

ISBN: (纸本)9798331530402

At present the white Light Emitting Diodes (LEDs) are mostly used light sources due to their extended lifespan, superior light output, and energy efficiency. This article presents an economical pulse-width modulation (PWM) dimming technique for LEDs to vary both the light output and the correlated color temperature (CCT) of the light source. The proposed approach provides a simple, stable, and inexpensive circuit design with adaptive PWM dimming method. A prototype luminaire consisting of two cool white and two warm white LED arrays has been developed and tested under low wattage conditions to verify the approach and its durability. This developed controller is compatible with the commercially available LED lamps and can function in various lighting scenarios. The study aims to demonstrate how the proposed PWM dimming technique can provide a tunable and dynamic LED luminaire. The relationship between the duty cycle and lighting parameters, including CCT, color rendering index (CRI), and illuminance are compared in this work. © 2025 IEEE.

关键词： Integrated circuit layout

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Design of a Scaled-Vehicle Research Platform for Software-Defined Vehicles

Design of a Scaled-Vehicle Research Platform for Software-De...

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11th international conference on Mechatronics and Robotics engineering, ICMRE 2025

作者： Oh, Sung Bhin Do, Young Soo Lim, Se Jeong Choi, Hyeok Jun Cha, Sung Keun Hong, Hyeong Keun Lim, Seong Hyeon Jeon, Jae Wook Sungkyunkwan University Department of Electrical and Computer Engineering Suwon Korea Republic of

ISBN: (纸本)9798331509293

Modern vehicles are integrated systems of complex software that support advanced features such as autonomous driving and over-the-air updates. Software-defined vehicles (SDVs) are emerging as a future automotive paradigm for managing increasing software complexity by centralizing computing resources and enabling flexible software updates and feature deployment. However, most SDV research is conducted in simulation environments because using real vehicles presents many challenges, including high cost, safety concerns, and implementation difficulties. In this paper, we present the design of an SDV research platform using a 1/5-scale vehicle model to overcome these limitations of SDV research. The platform implements a zone architecture and integrates various embedded systems to replicate the distributed computing environment of a modern vehicle. The platform allows researchers to experiment with different SDV concepts such as distributed computing, OTA updates, middleware, and vehicle software management without the constraints of full-scale vehicle testing. Our design demonstrates the feasibility of using extended vehicles for SDV research and provides insights into platform design for SDV research. © 2025 IEEE.

关键词： Distributed cloud

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