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检索条件"任意字段=Proceedings of the 3rd International Conference on Control and Computer Vision"

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i-Glove: An Intelligent Glove System Based on Deep Learning to Support Deaf-blind Individuals in Recognizing Banknotes 3

i-Glove: An Intelligent Glove System Based on Deep Learning ...

引用

3rd IEEE international conference on Robotics, Automation, Artificial-Intelligence and Internet-of-Things, RAAICON 2024

作者： Hossain, Fahad Mohammad Alavi, Rafit Safat, Yeamin Sarker, Gobinda Chandra Noor, Nafisa Hossain, Ekram Mymensingh Engineering College Department of Computer Science and Engineering Mymensingh Bangladesh University of Dhaka Department of Robotics and Mechatronics Engineering Dhaka Bangladesh

ISBN: (纸本)9798331534400

The deaf-blind community faces significant challenges in identifying banknotes due to simultaneous hearing and vision impairments, which complicate their ability to conduct daily financial transactions. Recent advances in Artificial Intelligence (AI)-based assistive technologies offer promising potential to address these challenges. This study presents the "i-Glove,"a wearable device specifically developed to assist the deaf-blind community in Bangladesh with accurate banknote identification. The i-Glove is designed to recognize nine common Bangladeshi banknotes (e.g., BDT 20, 50, 100) through a camera module integrated on the palmar side of the glove, which captures real-time images of the banknotes. These images are then processed by a convolutional neural network (CNN) model to accurately classify each banknote. Identified notes are translated into unique vibration patterns that are delivered to the user through a shaftless vibration motor embedded in the glove, providing intuitive, non-visual communication. Compared to previous approaches, our model demonstrates superior performance even with a compact dataset, achieving an overall F1-score accuracy of 96.55%, with class-specific precision, recall, and F1-score metrics ranging from 90% to 100%. Additionally, a dedicated application is developed which supports real-time banknote detection and interfaces seamlessly with the glove. The proposed system represents a significant step forward in assistive technology for the deaf-blind community, empowering the users with greater autonomy in financial transactions. © 2024 IEEE.

关键词： Convolutional neural networks

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Incentive Mechanism Of Distributed Electric Energy Transaction Based On Blockchain 3

Incentive Mechanism Of Distributed Electric Energy Transacti...

引用

3rd international conference on computer vision, Image and Deep Learning and international conference on computer Engineering and Applications, CVIDL and ICCEA 2022

作者： Wang, Zhiyu Zhang, Jing Changchun University of Science and Technology College of Computer Science and Technology Changchun China

ISBN: (纸本)9781665459112

The centralized electric energy transaction has deficiencies of large network overhead and high transaction cost, however, users trading electric energy in the distributed mode characterized by inactivity. Simultaneously, information disclosure easily occurs under complex transaction environment. Therefore, a distributed multi-party electric energy transaction incentive mechanism based on blockchain is proposed in this paper. According to the supply and demand relationship for electric energy, the transaction pricing model among multiple parties is established based on the auction theory, and the genetic algorithm is adopted to maximize the social welfare of participants in the distributed electric energy transaction. Meanwhile, the anonymous electric energy transaction is realized based on the blockchain, which can ensure the security of user transaction information to the greatest extent. The simulation results proved that the multi-party transaction incentive mechanism proposed in this paper can protect users' privacy and maximize social welfare of the energy transaction system. © 2022 IEEE.

关键词： Blockchain

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Vehicle Analysis System Based on DeepSORT and YOLOv5 3

Vehicle Analysis System Based on DeepSORT and YOLOv5

引用

3rd international conference on computer vision, Image and Deep Learning and international conference on computer Engineering and Applications, CVIDL and ICCEA 2022

作者： Guo, Fuheng Xu, Yi Shandong University of Technology School of Computer Science and Technology Zibo China

ISBN: (纸本)9781665459112

Nowadays, the constantly expanding coverage of expressways leads to an astronomical volume of daily high-speed traffic. In order to address the poor real-time performance of traditional traffic statistics and low accuracy in detection of densely distributed small targets for original algorithms, this paper proposes a vehicle analysis system that is based on DeepSORT and YOLOv5. More specifically, YOLOv5 is adopted to detect the target, Kalman filter is employed for prediction and update, and the Hungarian algorithm is applied for trajectory matching in the cascade matching, so as to realize the multi-target tracking of vehicles. Besides, inverse perspective mapping is performed to obtain the actual distance traveled by a vehicle per unit time, and to calculate the speed of it. The experimental results show that the vehicle analysis system based on DeepSORT and YOLOv5 has an average accuracy of 96% for vehicle targets, a 98.36% accuracy of vehicle speed measurement, and a lower model loss of than 2% on average, which meets the needs of real-time analysis. © 2022 IEEE.

关键词： Vehicles

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Design and Implementation of Five Stages Piplined RISC Processor on FPGA 3

Design and Implementation of Five Stages Piplined RISC Proce...

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： Ben Yousuf, Amani Najeeb Khaled Alamen, Dania Eljhani, Mohamed Muftah University of Tripoli Department of Computer Engineering Tripoli Libya

ISBN: (纸本)9798350319897

This research focuses on designing and implementing a processor with a five-stage pipeline for educational purposes. The proposed processor can execute five 16-bit instructions simultaneously and is designed and simulated using Verilog HDL. It is implemented on a Cyclone IV FPGA on the DE2i-150 design board. The processor is suitable for applications that require high processing speed and low power consumption, including mobile computers, consumer electronics, security systems, and more. This RISC-based processor has simple instructions that consume low power and execute quickly. © 2023 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Categorization of Butterflies using Convolutional Neural Network 3

Categorization of Butterflies using Convolutional Neural Net...

引用

3rd international conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2023

作者： Gill, Kanwarpartap Singh Sharma, Avinash Anand, Vatsala Gupta, Rupesh Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Department of Computer Science and Engineering Haryana Mullana-Ambala133207 India

ISBN: (纸本)9781665494007

Insects make up the incredible larger part of creature species on the globe, concurring to later studies, and their numbers are quick declining. Various insect species and geological regions have detailed this event, as there may be not sufficient data to decide its full scope. Insect population examination is challenging since the majority of checking procedures are wasteful and time-consuming. On the other hand, progresses in computer vision and deep learning might before long give new arrangements to this around the world issue. Entomologists may collect information always and non-intrusively at any time of day or season utilizing cameras and other sensors. Mechanized imaging can be utilized within the lab to record the physical characteristics of examples. Utilizing this data, a deep learning demonstrate may be made to figure the number, biomass, and kind of creepy crawlies. Deep learning models can too measure the variety in phenotypic characteristics, exercises. We may thank later advancements in computer vision and profound learning for the sudden increment in order to monitor insects using sensors and using prediction models. The proposed Sequential model for this work has an accuracy of 87 percent for batch sizes of value 128 and epochs of value 100. By utilizing this highly-trained prediction calculation, this demonstration can help entomologists in creating way better forecast models that can help within the categorization of butterflies and other insects. © 2023 IEEE.

关键词： computer vision

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Deep Learning and Proxy Smart Contract-Based Supply Chain Management for Electric Vehicles 3

Deep Learning and Proxy Smart Contract-Based Supply Chain Ma...

引用

3rd IEEE international conference on Power Electronics, Intelligent control and Energy Systems, ICPEICES 2024

作者： Gohil, Keyaba Gohil, Aditya Gupta, Rajesh Tanwar, Sudeep Inst. of Technology Nirma University Dept. of Computer Sci. and Engg. Ahmedabad India

ISBN: (纸本)9798350387193

In today's world of constant change and instant services, industrialisation has perhaps played the biggest role in the realisation of such a reality. The rapid and large-scale production of various goods is made possible through the concept of a supply chain. At the same time, in the world of automobiles, the advent of electric vehicles (EV) has revolutionalised the entire landscape by providing a much more energy-efficient and sustainable alternative. However, more than a supply chain, its proper management is more crucial to smooth functioning. Efficient supply chain management (SCM) in EVs is a very important step in ensuring that this novel technology can be made more cost-efficient and accessible. A viable remedy for these issues, considering the advancement in artificial intelligence and machine learning (AI/ML), blockchain, and other related technologies can be to integrate these solutions into the existing concepts of SCM and data storage. Encouraged by the aforementioned facts, we propose a deep learning (DL) based intrusion detection system (IDS) for EV manufacturing. We take into consideration artificial neural network (ANN), long short-term memory (LSTM), and recurrent neural network (RNN) algorithms and contrast and compare their performance on the data. The IDS is followed by a proxy smart contract (PSC) based deployment framework for smart contracts (SC), followed by secure storage of the supply chain data in a blockchain. The PSC solves the immutability aspect of blockchains whereas, the blockchain provides a secure and transparent storage solution, with efficient traceability. © 2024 IEEE.

关键词： blockchain technology data analytics Electric vehicles proxy smart contract suply chain management

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Rabble Based Autonomous Assistance Using Machine Learning Algorithms 3

Rabble Based Autonomous Assistance Using Machine Learning Al...

引用

3rd international conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Sutariya, Kamal Vishal Gupta, Mohan Lal, Bechoo Rahim Alatba, Sura Sriramakrishnan, G.V. Tripathi, Vikas Parul University Parul Institute of Engineering and Technology Department of CSE Gujarat Vadodara India Teerthanker Mahaveer University College of Computing Science and Information Technology Uttar Pradesh Moradabad India Department of CSE AP India Al-Turath Universiy College Computer Science Department Baghdad Iraq Mohan Babu University CSE Tirupati India Graphic Era Deemed To Be University Department of CSE Uttarakhand Dehradun India

ISBN: (纸本)9798350399264

In order to properly control rabbles, we shall investigate computer vision and mechanical aid technologies with lending devices here. Machine intelligence, commonly referred to as AI, or algorithms, enables software to improve prediction performance while requiring a deliberate goal to do so. Machine-learning algorithms anticipate new output using historical data as their input. Since information is so crucial, creating novel approaches for effectively administering the neighbourhood, pervasive data gathering systems of today is a crucial next stage for actors and thus is entirely independent. Therefore, deep learning and its autonomous rabbel control support network will be discussed here. With the availability of information expanding through time, education for application in numerous sectors has become more widespread. Many fields have benefited from the use of machine vision, encompassing research and academia database and process visualisation, biomedical imaging, and more. These methods have been applied to safety, computer components, internet websites, and mobile applications. Thus, we can draw an opinion regarding an autonomous assistance system for effective kernel maintenance that is based upon deep ***, COVID-19 is causing mayhem throughout the world. There have found over than 110 million cases, or the number grows daily. Due to the outbreak, or more 4 million people died. The three most affected nations are the Usa, India, and Brazil, and many agencies are working to develop a vaccine. The world is seeking get back to normal after a string of shutdowns while upholding safety precautions. As a consequence, it is necessary to keep an eye on anyone's hat and temperature within public spaces like malls, hospitals, offices, shrines, and the like. Costs increase as a consequence of the lengthy process and extensive contact with people. Consequently, a system is required that can detect respirators, gauge temperatures, and manage the crowd tha

关键词： computer vision

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BCI controlled Robot for Drones 3

BCI Controlled Robot for Drones

引用

3rd international conference on Smart Technologies, Communication and Robotics, STCR 2023

作者： Shanmuga Priyan, M. Arunachalam, A.R. Dharneesh, S.K. Tamilselvan, S. Bannari Amman Institute of Technology Ece Tamilnadu India

ISBN: (纸本)9798350370867

There is a significant progress in the field of brain computer Interface (BCI) technology in recent days which allows communication between human brain and external devices. This BCI technology can be used to control robotic systems such as drones using the power of thoughts. This BCI controlled robot aims to enable users to control a drone through their brain signals which provides more intuitive and efficient means of interaction. It includes many components like BCI hardware, signal processing techniques etc. The BCI hardware is responsible for acquiring the user's brain signals and converting them into digital signals that can be processed by a computer. Electroencephalography is a technique used to measure and record the electrical activity of the brain. The electrodes are placed on the scalp to detect the electric signals produced by the neurons in the brain. The meaningful information from the acquired brain signals are extracted using signal processing algorithms. These algorithms analyze the signals and detect relevant patterns and translate them into commands for drones. The robotic drone platform includes the drone itself with communication modules. The control commands generated by the BCI system are transmitted wirelessly to the drone which enables controlling the drone. This system has numerous potential applications including searching and rescue operations and surveillance. This BCI controlled robot for drones mainly highlights the integration of BCI technology with robotic systems to enable direct control of drones using brain signals. © 2023 IEEE.

关键词： Brain computer interface

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An emotional EEG signal classification research based on deep learning 3

An emotional EEG signal classification research based on dee...

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3rd international conference on computer vision, Image and Deep Learning and international conference on computer Engineering and Applications, CVIDL and ICCEA 2022

作者： Cai, Baoqing Quan, Wei Li, Qi Song, Yu Changchun University of Science and Technology School of Computer Science and Technology Changchun China Zhongshan Institute of Changchun University of Science and Technology Zhongshan China

ISBN: (纸本)9781665459112

For the task of classifying emotional EEG signals with rich high-dimensional features in the time and frequency domains, this paper proposes a novel deep learning algorithm, SincNet-E, inspired by the speech recognition model SincNet. The convolutional structure of SincNet is adapted so that it can be considered as consisting of two pooling layers alternately superimposed with three convolutional groups. Subsequently, the LSTM structure is added after the convolutional structure to enhance its extraction of time-dependent features in the signal data. This novel model effectively improves the classification performance of the deep learning algorithm for emotional EEG data, ultimately achieving an accuracy of about 83.89% without the need for manual feature extraction. © 2022 IEEE.

关键词： Convolutional neural networks

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System Cursor control Using Human Eyeball Movement 3

System Cursor Control Using Human Eyeball Movement

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3rd international conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Dhanasekar, J. Guru Aravindh, K.B. Kiren, A.S. Faizal Ahamath, A. Bharath Institute of Higher Education & Research Department of Mechatronics Engineering Tamilnadu Chennai India

ISBN: (纸本)9798350399264

This paper aims to develop a system for controlling the computer cursor using the movement of the user's eyeballs, providing a hands-free alternative to the traditional mouse. We developed a program using image processing techniques and machine learning algorithms in Python to obtain the eyeball movements and blink and translate them respectively into cursor movements and click actions. Our system was able to achieve a high level of accuracy in tracking the user's eye movements. Users were easily able to adapt to the new input method. This system has great potential to improve the accessibility and usability of computers for individuals with motor impairments or disabilities. This hands-free control method has great potential in the area of applications in gaming and virtual reality environment etc. © 2023 IEEE.

关键词： Python

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