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检索条件"任意字段=International Conference on Computer Technology and Development"

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A cascade classifier-based system for identifying And counting the different kinds of vehicles using Open CV 1

A cascade classifier-based system for identifying And counti...

引用

1st IEEE international conference on Advances in Computing, Communication and Networking, ICAC2N 2024

作者： Kumar, Amit Yadav, Sunita Galgotias University Department of Computer Science and Engineering Greater Noida India Galgotias University School of Computing Science and Engineering Greater Noida India

ISBN: (纸本)9798350356816

Vehicle identification and counting are becoming more important tools for highway management. Anyhow, because cars come in a variety of sizes, identifying them remains a test that directly affects the accuracy of vehicle counts. The advancements in vehicle detection technology have significantly progressed alongside the development of autonomous driving and intelligent transportation research. This study focuses on video-based algorithms for vehicle detection and counting, utilizing OpenCV technology as the foundation for these techniques. The suggested solution use the background subtraction method to identify foreground elements in a subsequent movie. Using OpenCV, Numpy, and object detection techniques, from those moving objects, automobiles are spotted, categorised, and counted for traffic estimation. The results of an experiment reveal that the proposed counting techniques are about 84.60% percent accurate. The method is able to provide good vehicle counting accuracy with quick calculation when combined with quick motion detection and tracking techniques. © 2024 IEEE.

关键词： Highway administration

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Design of new load security region analysis method for distributed photovoltaic development and consumption in distribution area 9

Design of new load security region analysis method for distr...

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9th international conference on Energy Materials and Electrical Engineering, ICEMEE 2023

作者： Li, Xiqin Zhang, Zhiyuan Zhao, Hu Tan, Jiuyu Zhang, Xiaojie State Grid Beijing Mentougou Electric Power Supply Company Beijing102300 China Beijing Smartchip Microelectronics Technology Company Limited Beijing102200 China

ISBN: (纸本)9781510672765

In order to avoid the influence of unbalanced load in distribution station area, resulting in economic losses in distribution station area, a new analysis method of load security region in distribution station area is proposed. Design the technical scheme of coordinated operation control of source, grid, load and storage for safe and efficient power supply in rural distribution station area, and collect multi-source data of load terminals in new distribution station area;According to the operation control architecture combining safe operation risk with flexibility and rigidity, the load balance objective function of the new distribution station area is calculated, and the load security region analysis of the new distribution station area is realized. The experimental results show that according to the actual state and monitoring results at different time points, the early warning information about the load safety region of the distribution station area is obtained. When the load of the new distribution station area is in the low-load scene, the voltage amplitude in this area changes little, while when it is in the high-load scene, the voltage amplitude changes greatly. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Photovoltaics Information security Analytical research computer security Power supplies Data acquisition Design and modelling Power grids Renewable energy Safety

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development of a quantitative evaluation system for static electricity induced luminescence using image proccesing 9

Development of a quantitative evaluation system for static e...

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9th international conference on Intelligent Informatics and BioMedical Sciences, ICIIBMS 2024

作者： Eguchi, Taiga Ishizu, Nanami Lee, Jin Yien Fujio, Yuki Fukuda, Osamu Kikunaga, Kazuya Saga University Faculty of science and engineering Saga Japan Sensing System Research Center Aist Tosu Japan

ISBN: (纸本)9798350363043

Static Electricity induced Luminescence (SEL) material (SrAl2O4: Eu2+) was recently discovered, which emits luminescence due to external energy from static electric. Static electric that could not be visualized can now be recognized through luminescence and SEL is expected to be a new image-based static electricity sensing technology. In this study, we developed a system to quantitatively evaluate SEL material using image analysis. The experimental results confirm correlation between the applied voltage and the maximum intensity of the SEL. © 2024 IEEE.

关键词： Strontium compounds

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Advancements, Methods, and Obstacles in Emotion Recognition with Multimodal Approaches 3

Advancements, Methods, and Obstacles in Emotion Recognition ...

引用

3rd international conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Arunkumar, M. Athiban, R. Selva Jothi, M. Pavithra, S. Dept of Computer Science and Engineering Chennai Institute of Technology Tamil Nadu India

ISBN: (纸本)9798331527549

Emotion recognition has gained an avid curiosity in the research area due to its broad range of applications in human-computer interaction particularly in real time emotion recognition, sentiment analysis, and affective computing. Deep learning techniques are advancing exponentially, automating feature engineering and transcending traditional machine learning techniques. Appeal of the above models can be highly beneficial but also raise certain technical and ethical concerns that are not often discussed enough in the existing studies. While highlighting the recent advancements, the methods involved and obstacles in emotion recognition, this review also proposes future directions in developing a standard unified framework for multimodal approaches. Categorizing and analysing the recent studies depends upon the model types employed, data modalities used and the type of fusion techniques used, this review was able to gain insights into the effect of recent multimodal approaches addressing technical and ethical concerns. Utilization of fusion techniques in multimodal models is still not reliable but they better convey the connection between different modalities and have a huge potential for development in the future. This review provides insights into the state of art multimodal methods using modalities like facial expressions, body gestures, vocal cues, text, and physiological signals for researchers to understand the trends and future directions in this field. © 2025 IEEE.

关键词： Contrastive Learning

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Workplace Wingman: Enhancing Indoor Autonomy for Efficient Workplace Operations 2

Workplace Wingman: Enhancing Indoor Autonomy for Efficient W...

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2nd international conference on Advanced Computing and Communication Technologies, ICACCTech 2024

作者： Potdar, Komal Mahajan, Yash Thakare, Ajinkya Amrutkar, Ruturaj Joglekar, Pushkar Vishwakarma Institute of Technology Department of Computer Engineering Maharashtra Pune India

ISBN: (纸本)9798331519056

This paper presents the 'Workplace Wingman,' an innovative autonomous system designed for workplace environments. Our solution integrates advanced features to optimize indoor operations. The system navigates curved roads with precision, maneuvers through roads with left and right turns, adjusts speed at stops, and employs a line-following mechanism for efficient path traversal. Furthermore, obstacle avoidance capabilities ensure safe navigation using Arduino technology. These features collectively enhance workplace efficiency, productivity, and safety. Our research contributes to the advancement of indoor autonomy, offering practical solutions to meet the evolving demands of modern workplaces. Innovatively, our system achieves autonomy without relying on Lidar, cameras, or Raspberry Pi, thus providing a cost-effective alternative without compromising performance or functionality. In addition to our development, we have reviewed and analyzed relevant research to enrich our understanding and inform our approach. The system's integration of diverse technologies demonstrates its adaptability and effectiveness in real-world workplace scenarios. © 2024 IEEE.

关键词： Motion planning

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An Investigation of Block Chains for Attaining Sustainable Society 3

An Investigation of Block Chains for Attaining Sustainable S...

引用

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

作者： Ramachandran, K.K. Lamba, Fit Lt Renu Rawat, Ruchira Gehlot, Anita Raju, Adusupalle Muni Ponnusamy, R. Dr G R D College of Science Management/Commerce/International Business India Graphic Era Deemed to Be University Department of Management Studies Dehradun India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun248002 India Uttaranchal University Uttaranchal Institute of Technology India India Chennai Institute of Technology Department of Computer Science & Engineering India

ISBN: (纸本)9798350399264

It's possible to define blockchain technology as the DLT-based technology upon which cryptocurrencies and other distributed ledgers rely. This innovation extends well beyond Bitcoin and other forms of digital money. With its help, a new Internet era may dawn in which sensitive information can be sent, stored, and managed without fear of tampering or other forms of corruption. Because of its potential to combat corruption and help the impoverished, among other things, this technology is worth investing in. Any kind of transaction, such as the sale of a home or a stock, may be tracked nearly instantly. Sustainable development is at the heart of today's modern world. technology like this may be useful in the pursuit of sustainability, which involves improving the here and now without jeopardizing the future. To be really useful, though, this innovation requires a robust digital governance structure. The purpose of this article is to investigate Blockchain technology as a tool for promoting long-term, environmentally friendly growth in India, and to identify contexts where it may be particularly useful. How the Indian economy may adopt this technology and incorporate it into its system to achieve Sustainable development is the topic of my paper. Capital market, accountable production and consumption, environmental protection, providing legal identity for everybody, property registration, and transparent philanthropy are all possible applications of this technology in India. The research methods used in this paper are entirely inductive, with a focus on secondary sources of information. © 2023 IEEE.

关键词： Smart contract

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Revolutionary Changes in Acute Lymphoblastic Leukaemia Classification: The Impact of Deep Learning Convolutional Neural Networks 2

Revolutionary Changes in Acute Lymphoblastic Leukaemia Class...

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2nd international conference on computer, Communication and Control, IC4 2024

作者： Singh, Retinderdeep Sharma, Neha Aggarwal, Priyanshi Singh, Mukesh Chythanya, Kanegonda Ravi Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Graphic Era Hill University Computer Science & Engineering Uttarakhand Dehradun248002 India Graphic Era Deemed to Be University Computer Science & Engineering Uttarakhand Dehradun248002 India Sr University School of Computer Science & Artificial Intelligence Warangal India

ISBN: (纸本)9798350387933

Blood cancers categorised as acute lymphoblastic leukaemia (ALL) pose a substantial threat to global public health and require extremely nuanced diagnostic techniques. This research study provides a substantial advancement in the field of blood cancer diagnosis through the development and implementation of an innovative Convolutional Neural Network model. On the basis of a large dataset of Blood Cells Cancer (ALL), which encompasses a variety of cellular morphologies associated with ALL, this model is constructed. The model under consideration is trained using deep learning methodologies and this dataset. The primary aim of this research endeavour is to improve the accuracy and reliability of blood cancer detection, a critical factor in facilitating timely and effective medical intervention. A fine-tuned CNN model is capable of identifying minute irregularities and patterns that may be detected in images of blood cells. This can assist the CNN model in distinguishing between benign and malignant cells accurately. To achieve higher degrees of specificity and sensitivity, the model's parameters are refined during the training process. The proposed CNN model exhibits an exceptional degree of performance, achieving an astounding accuracy rate of 96.92% after the training phase concludes. Blood cancer is accurately diagnosed with a substantial degree of precision by the model, which is substantial evidence of its extraordinary accuracy and underscores its potential as a critical diagnostic tool in clinical settings. © 2024 IEEE.

关键词： Neural network models

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Selective Temporal Knowledge Graph Reasoning 30

Selective Temporal Knowledge Graph Reasoning

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Joint 30th international conference on Computational Linguistics and 14th international conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Hou, Zhongni Jin, Xiaolong Li, Zixuan Bai, Long Guo, Jiafeng Cheng, Xueqi School of Computer Science and Technology University of Chinese Academy of Sciences China Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences China

ISBN: (纸本)9782493814104

Temporal Knowledge Graph (TKG), which characterizes temporally evolving facts in the form of (subject, relation, object, timestamp), has attracted much attention recently. TKG reasoning aims to predict future facts based on given historical ones. However, existing TKG reasoning models are unable to abstain from predictions they are uncertain, which will inevitably bring risks in real-world applications. Thus, in this paper, we propose an abstention mechanism for TKG reasoning, which helps the existing models make selective, instead of indiscriminate, predictions. Specifically, we develop a confidence estimator, called Confidence Estimator with History (CEHis), to enable the existing TKG reasoning models to first estimate their confidence in making predictions, and then abstain from those with low confidence. To do so, CEHis takes two kinds of information into consideration, namely, the certainty of the current prediction and the accuracy of historical predictions. Experiments with representative TKG reasoning models on two benchmark datasets demonstrate the effectiveness of the proposed CEHis. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Forecasting

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Secure and Efficient Certificateless Linearly Homomorphic Signature Scheme for Wireless Sensor Networks 2

Secure and Efficient Certificateless Linearly Homomorphic Si...

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2nd international conference on Big Data and Privacy Computing, BDPC 2024

作者： Zhu, Ting Shen, Limin School of Computer and Electronic Information Nanjing Normal University Nanjing China

ISBN: (纸本)9798350307597

With the development of network technology, wireless sensor networks (WSNs) have attracted widespread attention. However, in wireless sensor networks, sensor nodes are often distributed in harsh physical environments and communicate wirelessly with each other, so the data are vulnerable to tampering and forgery by third parties. Digital signature can be used as a security mechanism to solve the above problem. But the traditional digital signature technology needs to sign every message, which is not appropriate for sensor nodes limited by power and communication bandwidth. According to the practical application requirements of WSNs, this paper proposes a certificateless linearly homomorphic signature scheme for data transmission and authentication. The scheme can be used to ensure the authenticity, integrity and non-repudiation of data in WSNs. Furthermore, the security of the constructed scheme is proved in the random oracle model. The performance analysis shows that the scheme has certain advantages in overall performance. © 2024 IEEE.

关键词： Authentication Protocol

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AI Assisted Plant Disease Detection, Crop And Fertilizer Recommendation System 5

AI Assisted Plant Disease Detection, Crop And Fertilizer Rec...

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5th IEEE international conference for Emerging technology, INCET 2024

作者： Kumar, Raj Gupta, Sejal Srivastava, Yash Srivastava, Harsh Dept. of Computer Science KIET Group of Institutions Delhi- NCR Ghaziabad India

ISBN: (纸本)9798350361155

Agriculture is a cornerstone of India's economy, employing nearly half of its population and contributing significantly to its growth. Understanding the importance of nutrient management for crop productivity is paramount. However, Indian farmers face formidable challenges, including unpredictable irrigation patterns and poor soil quality, often lacking the necessary knowledge and resources for informed decision-making in crop selection and fertilizer use. Crop failures have profound consequences, affecting livelihoods and food security, while also posing risks to the environment. To address these challenges, our research presents an innovative solution in the form of an open-source, user-friendly web application. This application offers support for crop and fertilizer recommendations, a forecast of plant diseases, and an interactive news stream. Additionally, our approach incorporates interpretability techniques to elucidate predictions made by our disease detection model, making it a comprehensive tool for farmers and stakeholders in the agricultural sector. Our research endeavors to provide a practical and efficient solution to enhance crop production, thereby contributing to the sustainable development of India's agriculture and economy. © 2024 IEEE.

关键词： Recommender systems

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