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

共 18818 条记录，以下是401-410 订阅

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A Critical Analysis of Applying computer vision In Building an Intelligent System 3

A Critical Analysis of Applying Computer Vision In Building ...

引用

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

作者： Ballari, Syed Omar Srinivas, Angalkuditi Gupta, Manish Dhobal, Kiran Akabarkhan, Pathan Shahnavajkhan Reddy, Dasari Veera Guru Nanak Institutions Technical Campus Department of Civil Engineering Telangana Ibrahimpatnam501506 India Koneru Lakshmaiah Education Foundation Department of CSE India Lovely Professional University Phagwara India Uttaranchal University Uttaranchal Institute of Technology India Sankalchand Patel University Shri C.J. Patel College of Computer Studies Faculty of Computer Science India SR University School of Computer Science and Artificial Intelligence Telangana Warangal India

ISBN: (纸本)9798350399264

The terminology "computer vision"refers to the method that leverages technologies of intelligent systems such as artificial intelligence (AI) to enable computers to gather useful information from visual sources. The automated activities are demonstrated previously using computer vision understanding. The definition, examples, as well as uses of computer vision, are covered in this article. For computer vision to be totally successful there must be a huge collection. When they lack the knowledge required to execute the task at hand, these systems periodically discover trends, which cause this to occur. Hence, the research has evaluated the notion of computer vision in diverse fields of operations through the literature review as well as in the analysis and discussion portion of the study. Since the literature review and data analysis of the research is done through secondary sources, an imperative notion of review has been gathered and presented. Therefore, the significance of computer vision in assembling intelligent systems like AI and other new technologies has given discussed in the research. © 2023 IEEE.

关键词： Intelligent systems

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CNN Approach for Live Speech Emotion Detection 3

CNN Approach for Live Speech Emotion Detection

引用

3rd international conference on Electronics and Renewable Systems, ICEARS 2025

作者： Subramani, Nevedha Sivasankar, Srividhya Saravanan, K. Sakthivel, K. K. S. Rangasamy College of Technology Tiruchengode India Computer Science and Business Systems K. S. Rangasamy College of Technology Tiruchengode India

ISBN: (纸本)9798331509675

The application of convolutional neural networks (CNNs) in real-time speech recognition in real-time speech improves the real-time processing capability and the ability to accurately and effectively control speech in many places. CNNs are useful for this task because they can learn complex features from noise sources that represent the frequency and amplitude of sounds over time. Using multiple convolutional techniques, these networks can capture spatial and temporal patterns in audio data, making them very good at distinguishing loud speech. This approach is particularly useful for applications in smart assistants, fast change services, and hearing aids, where immediate detection and response are important. The main advances include the development of well-designed models and training methods to increase model accuracy and speed. These models can be further developed to recognize specific sounds, tones, or words to provide personalized experiences for users. As commercial performance improves, CNNs for instant speech recognition have become easier to use, paving the way for widespread use of equipment, security, and technology among humans. © 2025 IEEE.

关键词： Convolutional neural networks

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Exploring Data Augmentation Effects on A Singular Illumination Distribution Dataset with ColorJitter 3

Exploring Data Augmentation Effects on A Singular Illuminati...

引用

3rd international conference on Image Processing and Media Computing (ICIPMC)

作者： Xiao, Jianqiang Guo, Weiwen Liu, Junfeng South China Univ Technol Guangzhou Peoples R China Hitachi Elevator China Co Ltd Guangzhou Peoples R China Hitachi Bldg Technol Guangzhou Co Ltd Guangzhou Peoples R China

ISBN: (纸本)9798350386660;9798350386677

This paper explores the impact of data augmentation via ColorJitter on the generalization capabilities of deep learning models trained on the Single Illumination Distribution dataset (SID). By systematically manipulating brightness, contrast, saturation and hue, our study reveals that while enhancements in saturation and contrast yield minimal improvements, adjustments in brightness and hue significantly increase model accuracy. However, even the most effective augmentations cannot elevate the overall model performance to a practically viable level, highlighting the limitations of training with restricted lighting diversity. Moreover, our comparative analysis across convolutional neural networks (CNN) and Transformer architectures under these conditions indicates that Transformers require higher data quality and quantity for optimal performance. These findings emphasize the necessity of incorporating rich, real-world visual features into training datasets. Also, data augmentation strategies for visual Transformers require further research to fully optimize their performance in different visual environments.

关键词： Data Augmentation computer vision Generalization

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Application and research of intelligent inspection robots in hydropower stations 3

Application and research of intelligent inspection robots in...

引用

3rd international conference on Electronic Information Engineering, Big Data, and computer Technology, EIBDCT 2024

作者： Huang, Yingying Cao, Hanhua Gu, Changle Guangdong Huaxia Senior Technical School Guangzhou510935 China Guangzhou Xinhua University Guangzhou510520 China

ISBN: (纸本)9781510680449

A machine vision based inspection robot system is designed in this paper to address the issues of high cost and difficulty in ensuring detection accuracy in traditional manual pumped storage station crack and seepage detection. Construct a convolutional neural network that integrates cross entropy and Dice cost function, and establish an evaluation function based on total pixel accuracy, intersection to union ratio, and F1 score to ensure accurate detection of common cracks. In order to verify the effectiveness of the robot inspection system, the convolutional neural network was tested and compared with common computer vision and manual detection methods in terms of performance. The comparison results show that the neural network constructed in the article has made significant progress in both detection accuracy and detection efficiency. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： computer vision

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Enhancing DC Microgrid Performance: A Comprehensive Review of control, Operation, and Protection Strategies 3

Enhancing DC Microgrid Performance: A Comprehensive Review o...

引用

3rd IEEE international conference on Electrical Power and Energy Systems, ICEPES 2024

作者： Gautam, Abhiraj Gangodkar, Durgaprasad Lohumi, Yogesh Ghazi, Mohd Rehan Graphic Era Deemed to be University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350390728

This research paper presents a comprehensive review of key aspects related to DC microgrids, drawing insights from multiple scholarly sources. It encompasses sensitivity analysis of conversion losses, control strategies, stabilization techniques, power architectures, applications, standardization issues, autonomous control based on voltage variation, protection mechanisms, hierarchical control implementation, and primary and secondary control. By synthesizing findings from these diverse sources, this paper aims to provide a holistic understanding of DC microgrid performance enhancement. The analysis covers various dimensions, including operation, control, and protection, offering valuable insights for researchers and practitioners in the field of microgrid technology. © 2024 IEEE.

关键词： Microgrids

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Paintings vs Photos Classification Using Deep Learning 3

Paintings vs Photos Classification Using Deep Learning

引用

3rd international conference on Technological Advancements in Computational Sciences, ICTACS 2023

作者： Agarwal, Aryan Ratra, Aryan Vats, Satvik Sharma, Vikrant Singh, Sunny Singh, Karan Graphic Era Hill University Computer Science Engineering Dehradun India Nextgen Techedge Pvt. Ltd. India School of Computer and System Science Jawaharlal Nehru University New Delhi India

ISBN: (纸本)9798350342338

Identifying a picture's content based on its attributes is a fundamental task in computer vision known as image classification. In this article, we provide a study on the use of machine learning algorithms to categorize images of paintings and photographs. We investigate the performance of different models, such as decision trees, convolutional neural networks, and support vector machines, on this problem. We also look into how data preprocessing methods and hyperparameter tuning affect how well the models perform. According to the results of our experiments, CNNs classify artworks and photographs with an accuracy of 98%, which is the highest. © 2023 IEEE.

关键词： computer vision convolutional neural networks decision trees hyperparameter tuning image classification paintings performance support vector machines

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Research on commodity image detection based on improved YOLOv5 3

Research on commodity image detection based on improved YOLO...

引用

3rd international conference on computer vision and Data Mining, ICCVDM 2022

作者： Lv, JiaPeng Yang, DeGuo School of software College Shenyang University of Technology China

ISBN: (纸本)9781510661363

In order to solve the problem of false detection and missing detection caused by different shapes and scales of commodities in commodity image detection, a commodity image detection algorithm based on improved YOLOv5 was proposed. Firstly, the algorithm optimizes the extraction features of Backbone by adding Transformer structure to Backbone network of YOLOv5. Then, the original PANet structure of Neck network is replaced by BiFPN structure, and the coordinate attention mechanism is introduced, so that the new network model (CA-BIFPN) can detect and locate the position of goods in the image more accurately. In order to verify the effectiveness of the improved method, a comparative experiment is conducted with YOLOv5. Experimental data show that the improved YOLOv5 algorithm proposed in this paper achieves multi-scale target detection, and the mAP reaches 99.5% on the self-made dataset, which is 0.2% higher than the original YOLOVv5 algorithm. © COPYRIGHT SPIE.

关键词： computer vision

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Perception-Map Generation for Autonomous Driving Vehicle 3

Perception-Map Generation for Autonomous Driving Vehicle

引用

3rd international Workshop on Intelligent Systems, IWIS 2023

作者： Kim, Kwanho Jo, Kanghyun School of Electical Engineering University of Ulsan Ulsan Korea Republic of Dept. of Electrical Electronic and Computer Engineering University of Ulsan Ulsan Korea Republic of

ISBN: (纸本)9798350305043

With the development of deep learning technology, algorithms related to computer vision used for autonomous driving are becoming faster and more accurate. The software architecture of autonomous driving consists of perception, decision, and control stages. In this paper, the perception stage is composed by combining several sensors and algorithms. In the perception stage, obstacle recognition and traffic signal detection are main tasks for path determination. This work creates a map that includes all of this information, helping more efficient determination in the decision stage. The experiments were conducted using a 3D simulator with ROS-noetic. The performance of obstacle recognition is evaluated for accuracy, recall, precision by confusion matrix. This work achieves 95.6% of accuracy, 88.6% of recall, 76.6% of precision. The experiments of traffic light detection task are evaluated as error ratio of distance estimation by stereo vision. Average error rate was calculated as 7.25%. © 2023 IEEE.

关键词： Autonomous vehicles

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Investigation on Correlation of Water Quality Data with Aerial Images 3

Investigation on Correlation of Water Quality Data with Aeri...

引用

3rd international conference on Digital Transformation and Applications, ICDXA 2024

作者： Suandi, Dani Saputra, Dany Eka Michael, Petra School of Computer Science Bina Nusantara University Computer Science Jakarta Indonesia

ISBN: (纸本)9798350373424

Maintaining good water quality is fundamental for successful and sustainable pond fish farming. It directly affects the health, growth, and overall well-being of the fish population and contributes to the overall success of the aquaculture operation. Therefore, periodic control of water quality is highly recommended. The forthcoming methodology aims to assess water quality using aerial imagery. Nevertheless, to implement this approach, an initial inquiry is required to examine the correlation between aerial imagery and sensor data. In this scenario, data comprising TDS, pH, and temperature is acquired using manual sensors. Simultaneously, aerial images are captured using drones at different altitudes. Two approaches are employed to extract features from these aerial images: one involves determining the dominant eigenvalues of the image pixel matrix, and the other employs matrix convolution techniques, incorporating kernel matrices and max pooling matrix techniques. Subsequent to extracting the image feature data, correlation analysis is performed using the Spearman method. The result shows that there is a weak correlation between grayscale image and TDS level at 0.1 from eigenvalues method, and -0.30 from convolution method. © 2024 IEEE.

关键词： Water quality

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Enhancing Reliability and Performance of Hybrid (PV and SEGP) Energy Island Microgrid Systems for Community Modernization 3

Enhancing Reliability and Performance of Hybrid (PV and SEGP...

引用

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

作者： Kabir, Kazi Meharajul Binzaid, Shuza Prairie View A&m University Electrical and Computer Engineering Department TX United States

ISBN: (纸本)9798350387193

In response to escalating energy demand and environmental concerns, renewable energy sources have emerged as crucial alternatives to conventional power generation. This paper proposes an innovative solution to address reliability and performance challenges in renewable hybrid PV and Sustainable Energy Generating Pad (SEGP) energy systems by integrating power electronics devices connected to the AC-DC microgrid system. The study uses ETAP software for simulation to identify Busbar instability and the system's performance. Subsequent adjustments to the power electronics devices result in notable system reliability and performance enhancements of about 98-100%, leading to reduced power losses. These findings underscore the transformative potential of this approach in bolstering societal sustainability by sustaining renewable electricity generation and mitigating environmental impacts. The research significantly contributes to ongoing efforts to bridge the gap between energy supply and demand for stable island mode microgrid operation mechanisms, addressing challenges associated with renewable energy generation with alternative energy source methods. © 2024 IEEE.

关键词： Hybrid Energy Microgrid SEGP Voltage Reliability

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