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Machine Learning-based Dynamic signal Switching: A Promising Solution to Traffic Congestion

Machine Learning-Based Dynamic Signal Switching: A Promising...

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2023 international conference on Innovative Computing, Intelligent Communication and Smart Electrical systems, ICSES 2023

作者： Kanchana, M. Gopirajan, P.V. Mahalakshmi, B. Vijaya Nirmala, B. SRM Institute of Science and Technology School of Computing Department of Computing Technologies Katankulathur Tamil Nadu Chennai603203 India SRM Institute of Science and Technology School of Computing Department of Computational Intelligence Katankulathurx Tamil Nadu Chennai603203 India AMC Engineering College Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350319200

Today's growing urban population means increased revenue for individuals, translating into growing vehicles on the road. Nowadays, people use their private vehicles instead of public transportation, which results in a considerable number of personal vehicles that lead totraffic congestion everywhere. The ever-increasing number of vehicles and complex congestion leads to frequent traffic jams in major cities. In today's scenario, traditional traffic management methods have become redundant as the traffic volume has grown exponentially. The primary goal of this proposed work is to develop an algorithm that uses machine learning to control traffic effectively and ensure efficient traffic flow in the event of unforeseen events like accidents. The existing algorithm focuses on predicting shortterm traffic flow but ignores that traffic congestion may also occur due to accidents and emergencies. Our proposed model will consider all the above factors and use dynamic signal switching among lanes to predict the best and most efficient solution to reducing waiting time for vehicles and congestion on the road. To create an effective traffic flow management model with the least amount of road mayhem, our suggested model needs traffic data as input, which was then trained using various Machine Learning (ML) models. © 2023 IEEE.

关键词： IDD image processing Machine Learning Neural Network RCNN Traffic Management YOLO

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image Processing and Control of Tracking Intelligent Vehicle based on Grayscale Camera 5

Image Processing and Control of Tracking Intelligent Vehicle...

引用

5th IEEE international conference on image Processing Applications and systems (IPAS)

作者： Zhang, Jian Liu, Yufan Li, Ao Zeng, Jinshan Xie, Hongtu Sun Yat Sen Univ Sch Elect & Commun Engn Shenzhen Campus Shenzhen Peoples R China Nanchang Hangkong Univ Sch Informat Engn Nanchang Jiangxi Peoples R China

ISBN: (纸本)9781665462198

In order to realize the rapid and stable recognition and automatic tracking of various complex roads by the intelligent vehicles, this paper proposes image processing and cascade Proportion Integration Differentiation (PID) steering and speed control algorithms based on CMOS grayscale cameras in the context of the national college student intelligent vehicle competition. First, the grayscale image of the track is acquired by the grayscale camera. Then, the Otsu method is used to binarize the image, and the information of black boundary guide line is extracted. In order to improve the speed of the race, various track elements in the image are identified and classified, and the deviation between the actual centerline position and the ideal centerline position of the intelligent vehicle is calculated. Third, the discrete incremental cascade PID control algorithm is used to calculate the pulse width modulation (PWM) signal corresponding to the deviation. And the PWM signal is acted on the steering motor through the driving circuit, driving the intelligent vehicle to always drive along the middle road, so as to achieve the purpose of automatic tracking guidance. Experiments prove that the intelligent vehicle of this design can identify complex roads quickly and in a stable way, accurately complete automatic tracking, and obtain higher speed performance.

关键词： tracking intelligent vehicle proportional integral derivative control CMOS grayscale camera binary image image processing

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Research of technology About Video Control based on Real-Time Transmission

Research of Technology About Video Control Based on Real-Tim...

引用

international conference on Information systems and Computer Aided Education (ICISCAE)

作者： Haoxue Wang Jinglan Li Huaiqiang Liu Linyi University Linyi China

ISBN: (数字)9798350350760

ISBN: (纸本)9798350350777

With the increasing demand for multimedia on the internet, video technology has gradually become the mainstream of multimedia transmission on the internet. In order to avoid overflow and underflow of buffer in transmission and to ensure the continuity of image of human visual pair, this paper proposes an algorithm to force the transmission rate to be adjusted, considering that the video bit rate cannot be completely the same as the change of network bandwidth. Combining with the characteristics of VTP adaptive coding and packaging scheme, an improved packaging scheme is proposed for real-time video control. The experimental results of end-to-end video transmission system show that video transmission control technology can improve packet loss rate and real-time transmission.

关键词： Visualization Force Bit rate Packet loss Bandwidth Streaming media Packaging Real-time systems internet Information systems

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Intelligent Fault Diagnosis of Transformer based on Infrared image and Mask RCNN 4

Intelligent Fault Diagnosis of Transformer Based on Infrared...

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4th international conference on Smart Power and internet Energy systems (SPIES)

作者： Sun, Lintao Wang, Jianjun Liu, Jiangming Zhang, Xuanzhe Li, Wenyan Guo, Chuangxin Maintenance Co State Grid Zhejiang Elect Power Co Prod Command Ctr Hangzhou Peoples R China Maintenance Co State Grid Zhejiang Elect Power Co Hangzhou Peoples R China Maintenance Co State Grid Zhejiang Elect Power Co Substn Maintenance Ctr Hangzhou Peoples R China Zhejiang Univ Coll Elect Engn Hangzhou Peoples R China

ISBN: (纸本)9781665489577

The safe and stable operation of the transformer is of great significance to the power grid. In order to improve the efficiency of transformer diagnosis, this paper proposes an intelligent transformer fault diagnosis method based on masked RCNN. First, during operation and maintenance, infrared images of transformers are collected and marked to complete the preliminary construction of the data set. To alleviate the imbalance between positive and negative samples, the number of negative samples is expanded by rotation, scaling, clipping and translation, and a GHM loss function is introduced. In order to meet the requirements of real-time detection. Comparative experiments show that, compared with the original model, the improved Mask-RCNN has higher diagnostic accuracy and lower false positive rate. The fault diagnosis rate was 86.72%, and the false positive rate was 7.68%. It can accurately realize intelligent fault diagnosis of transformers, and has certain engineering value for smart grid construction.

关键词： transformer infrared image intelligent fault diagnosis Mask-RCNN

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A Low-Complexity Transceiver Design and Prototype Development for Narrowband IoT 7

A Low-Complexity Transceiver Design and Prototype Developmen...

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7th international conference on Computer and Communication systems, ICCCS 2022

作者： Zhang, Ruiqi Wu, Peiran Wen, Wenkun Xia, Minghua Sun Yat-sen University School of Electronics and Information Technology Guangzhou510006 China Guangzhou Techphant Co. Ltd. Guangzhou510310 China

ISBN: (数字)9781665450607

ISBN: (纸本)9781665450607

In this paper, a low-complexity transceiver is designed for narrowband internet-of-Things (IoT). Its prototype is developed based on GNU Radio, an open-source software-defined radio development toolkit. To deal with potentially high carrier-frequency offsets and low received signal-to-noise ratio widely occurring in IoT, we adopt the chirp signals as the preamble and the modulation scheme of direct sequence spread spectrum-continuous phase frequency shift keying (DSSS-CPFSK) for the payload. Given this transmitter, the receiver is carefully designed, especially including the frame synchronization and payload demodulation. Afterward, the prototype of this transceiver is implemented in GNU Radio. Finally, simulation results in Matlab and field test ones based on GNU Radio and USRP demonstrate the effectiveness of the proposed design and prototype development. © 2022 IEEE.

关键词： internet of things

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Per-Channel image Super Resolution

Per-Channel Image Super Resolution

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international IEEE conference on signal-image Technologies and internet-based System

作者： George Kamal Milad Ghantous Department of Media Engineering and Technology Faculty of Engineering German University in Cairo Cairo Egypt

Single image Super Resolution (SISR) is one of the essential tasks in the image processing field, which aims to enhance the resolution of images. With the aid of Deep Learning (DL), SISR recently has made significant improvements and achieved promising *** paper introduces a novel training technique, called Per-Channel training. This novel training technique proved to obtain the best results in terms of the common Super Resolution (SR) metrics across all testing datasets used, reaching a maximum average Peak signal-to-Noise Ratio (PSNR) of 39.34 dB and Structural Similarity Index Measure (SSIM) of 0.9714 in one of the test datasets.

关键词： Training Measurement Deep learning PSNR image color analysis Superresolution Indexes

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An Advanced Edge Intelligent Approach for Capsule Defect Recognition based on CNN Using an Embedded Platform

An Advanced Edge Intelligent Approach for Capsule Defect Rec...

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2023 international conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2023

作者： Zhou, Junlin Wu, Qun Wang, Xindi Ding, Xiang Lu, Yihuai Liu, Yongbin School of Environmental Science and Optoelectronic Technology University of Science and Technology of China Hefei China Beijing Hy Orient Detection Technology Co Ltd. Beijing China Internet of School Anhui University Hefei China School of Electrical Engineering and Automation Anhui University Hefei China Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China Smart Grid Digital Collaborative Technology Joint Laboratory of Anhui Province Hefei China

ISBN: (纸本)9798350318012

The capsule, as a carrier of medicine, plays a crucial role in protecting drugs, facilitating gastrointestinal absorption, and enhancing their efficacy. To ensure the quality of capsules, it is essential to identify and remove any defects present on their surface. Traditional inspection methods have often been time-consuming and resource-intensive. However, by leveraging optimized neural network architecture and advanced end-equipment, it is now possible to significantly improve inspection efficiency and resource compatibility. In this study, we propose a novel approach to defect detection on capsules using a lightweight Convolutional Neural Network (CNN) model integrated into an embedded system. This model is designed to adapt to different workload conditions and drug types, thereby enhancing detection efficiency. By exploiting the capabilities of the embedded system, we shift the image processing task to the edge, effectively tackling the inherent problems associated with processing delay, privacy, and load that are prevalent in traditional modes. © 2023 IEEE.

关键词： Embedded systems

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Multimodal Sign Language and Big Data Integration Research

Multimodal Sign Language and Big Data Integration Research

引用

Communication, image and signal Processing (CCISP), international conference on

作者： Fengqian Song Huiyu Yang Yangyang Zhang Internet Academy Anhui University Hefei China Daguan Data Co. Ltd. Shanghai China

ISBN: (数字)9798350356656

ISBN: (纸本)9798350356663

Sign language is the primary means of communication for the deaf and mute community. The regional and national differences in sign language have led to barriers between different sign language systems, making communication between deaf and mute individuals from different regions challenging. This paper proposes a vision-tactile fusion approach to recognize sign language. The scheme applies a flexible sensor data glove to monitor the angle changes of finger joints, as well as visual image processing technology, to integrate tactile and visual data for sign language recognition. The integration is performed through three methods: weighted average, weighted multiplication, and attention weights, with accuracy rates of 95.55%, 97.87%, and 98.83%, respectively.

关键词： Sign language Visualization image recognition Accuracy Sociology signal processing algorithms signal processing Feature extraction Pattern recognition Sensors

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The Convergence of Artificial Intelligence, internet of Things, and Healthcare: Legal Considerations for a Connected Future 5th

The Convergence of Artificial Intelligence, Internet of Thin...

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5th international Ethical Hacking conference, eHaCON 2024

作者： Ghosh, Jayanta Sinha, Vijoy Kumar Nanda, Ardhendu Sekhar The West Bengal National University of Juridical Sciences Kolkata India Centre for Regulatory Studies Governance and Public Policy The West Bengal National University of Juridical Sciences Kolkata India National Institute of Securities Markets and Maharashtra National Law University Mumbai India

ISBN: (纸本)9789819784561

AI and IoT may supplant human actions, and results have had a more profound impact on bioethics across the globe. technology-based healthcare using AI and IoT has exploded in the global health business. Human-to-human care has succeeded in many domains, from industrial efficiency to human life. Gaps formed between the human psyche to allow AI and IoT may be scrutinized, and ethical problems raised. Initial testing revealed loopholes in meta-data collecting, threatening digital privacy, and disrupting healthcare protection and insurance. A minor error can cost a human life. Low risk of physical injury, precise outcomes, and speedier healthcare data governance make IoT services popular. Big data ensures unpredictability in data handling cloud storage solutions, which may be very confidential. Government regulations may struggle to maintain unique health IDs and considerable tracking of health services. The newest applications of mind-based deductions to real life put both parties’ mental health at risk. The global market for digital healthcare has surpassed 5.5 billion USD. The healthcare industry is trying hard to replace human intervention with human growth and development. AI and IoT technologies are available to aid healthcare practitioners with administrative activities, clinical documentation, patient outreach, image analysis, medical device automation, and remote patient monitoring. This research will examine AI and IoT in healthcare, both from a practical and international legal standpoint. The international legal scenario will help to make a synthetic analysis for future legal directions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Electronic health record

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image inpainting based on directional Gaussian graph model using multi-head reference 13

Image inpainting based on directional Gaussian graph model u...

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13th international conference on signal Processing systems, ICSPS 2021

作者： Zhang, Zhonghao Ma, Lihong Dept. of Electronic & Computer Engineering The Hong Kong Univ. of Science & Technology Clear Bay Hong Kong School of Electronic & Information Engineering South China Univ. of Technology 386 Wushan Rd. Guangzhou China

ISBN: (数字)9781510653184

ISBN: (纸本)9781510653177

This paper aims to repair missing regions which are corrupted along arbitrary directions. It presents a mixed image inpainting method based on Markov random field. By using Belief Propagation scheme in low gray-levels and alternately suggesting a directional Gaussian Graphical model (DGGM) for multiple references in a high-level range, it gains a balance between the model accuracy and the computation complexity in realization. On the basis of an existing method in [1], it improves the method in high level inpainting for the task under small train sets and large corrupted regions, by introducing these multi-head reference clues. Experimental results are given, the inpainting quality of different kinds of images with different sizes and contents under different parameter settings are compared in metrics of the peak signal noise ratio and the structural similarity index. The significance of parameter settings and the efficient computational cost could demonstrate the feasibility of this method. © COPYRIGHT SPIE.

关键词： Belief propagation

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