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检索条件"任意字段=2023 International Conference on Computer Science and Automation Technology, CSAT 2023"

共 68649 条记录，以下是4711-4720 订阅

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Calorie Recognition from Food Images Using CNN for Nutritional Analysis

Calorie Recognition from Food Images Using CNN for Nutrition...

引用

2023 international conference on Data science, Agents and Artificial Intelligence, ICDSAAI 2023

作者： Guru, R. Pavithra Ayyadurai, M. Amirthalakshmi, T.M. Neelaven, R. Sujatha, K. Srm Institute of Science and Technology Department of Electronics and Communications Engineering Ramapuram Campus Chennai89 India Srm Institute of Science and Technology Department of Computer Science and Engineering Ramapuram Campus Chennai89 India

ISBN: (纸本)9798350348910

In recent years, people tend to consume excess junk food and are unaware of the calories taken. To have a healthy diet, you need to calculate your calorie count before eating. We have developed a calorie management system using deep learning algorithms from images provided by users to enable users to track their daily calorie intake. It can be used for daily calorie tracking for health enthusiasts. It can also provide information about food ingredients. This project uses the Gray Level Co- occurrence Matrix and the Discrete Wavelet Transform. © 2023 IEEE.

关键词： Discrete wavelet transforms

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TrilemmaGuard: Safeguarding against the Challenges Posed by Blockchain Trilemma 26

TrilemmaGuard: Safeguarding against the Challenges Posed by ...

引用

26th international conference on computer and Information technology, ICCIT 2023

作者： Shafin, Khandakar Md Reno, Saha University of Science and Technology Bangladesh Army International Department of CSE Cumilla Bangladesh

ISBN: (纸本)9798350359015

Current blockchain consensus models provide targeted solutions but often struggle to find a balance. While certain methods prioritize decentralization, they may compromise security or operational efficiency, and vice versa. This research employs state-of-the-art methodologies to create a novel consensus model that addresses the intricate aspects of the blockchain triad. By utilizing a verifiable random function (VRF) and dynamic reassessment of stake, the impartiality of slot leader selection is ensured. Through skillful implementation of batch agreement systems, consensus on transaction groups is rapidly achieved. Mechanisms like the Honey Badger Byzantine Fault Tolerance (BFT) protocol, sharding and secondary-layer solutions also contribute to the elevation of scalability. Collectively, these advancements establish a strong consensus model that adeptly navigates the complexities of decentralization, security, and scalability within blockchain frameworks. © 2023 IEEE.

关键词： Blockchain Consensus Decentralization Scalability Security Trilemma

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Brain Tumor Detection using CNN

Brain Tumor Detection using CNN

引用

2023 international conference on System, Computation, automation and Networking, ICSCAN 2023

作者： Brindha, R. Poornima P, U. Pongiannan R, K. Franklin, J. Subramanian, Malavika Angayarkanni, V. Srm Institute of Science and Technology Department of Computing Technologies Kattankulathur India Srm Institute of Science and Technology Department of Electrical and Electronics Engineering Kattankulathur India

ISBN: (纸本)9798350315127

The second most common cause of cancer today is a tumour. To detect tumours like brain tumour, the medical field needs a quick, automated, effective, and reliable technique. A crucial part of treatment is detection. Doctors keep a patient out of danger if accurate tumour detection is possible. This application makes use of several image processing methods. Using this application, doctors are able to properly treat a large number of tumour patients and save their lives. Simply put, a tumour is an accumulation of uncontrolledly expanding cells. The development of brain tumour cells causes brain failure because they eventually eat up all the nutrients meant for healthy cells and tissues. To determine the location and size of the patient's brain tumour, doctors manually review the patient's MR images of the brain. This is time-consuming and results in inaccurate tumour detection. A tumour is an uncontrollably expanding mass of tissue. A Deep Learning architecture that combines CNN (Convolution Neural Network), also referred to as NN (Neural Network), and VGG can be used to identify brain tumours. Transfer learning. Its main strength is the model's ability to predict whether a tumor is present in an image. Returning is yes if the cancer is present and no if it is not. © 2023 IEEE.

关键词： Tumors

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Object Size Recognition as Intra-class Variations using Transfer Learning

Object Size Recognition as Intra-class Variations using Tran...

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2023 international conference on computer science, Information technology and Engineering, ICCoSITE 2023

作者： Rahmania, Rissa Hendric Spits Warnars, Harco Leslie Soewito, Benfano Gaol, Ford Lumban Bina Nusantara University BINUS Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350320954

The ability to differentiate various products in the retail store plays an essential role to provide effectiveness to customers and reduce or even eliminate long queues. However, traditional machine learning algorithms are incapable of recognizing many subordinate categories in various retail product. This paper aims to recognize the retail product recognition algorithm based on the YOLOv7 model in terms of intra-class variations, with the sub-categories of brand and size. We used two schemes of the dataset to compare recognition performance between them. Firstly, the YOLOv7 is applied in the two schemes of the dataset that is annotated with the subordinate category to detect the brand as meta category. Secondly, the proposed method is applied by adding the object size classification into the YOLOv7 model where the square area of the bounding box was calculated to classify the product according to size. Confidence score and square area are used to verify the object and to obtain the product size, which represents sub-category of the product. The experimental results show that our proposed method achieves higher recall compared to baseline object detection. © 2023 IEEE.

关键词： Object recognition

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Integration of PLC and Robotic Operating System for Enhanced automation Efficiency' 2

Integration of PLC and Robotic Operating System for Enhanced...

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2nd IEEE international conference on Futuristic Technologies, INCOFT 2023

作者： Saxena, Aditi Ali, Aqeel Abdulsada, Zainab. R. School of Technology Department of Mechatronics Woxsen University Komkole Hyderabad502345 India Medical Technical College Al-Farahidi University Iraq National University of Science and Technology Dhi Qar Iraq

ISBN: (纸本)9798350308846

The mix of Robotic Operating System (ROS) and Programmable Logic Controllers (PLCs) has showed promise in improving automation effectiveness in a range of industrial uses. In order to achieve seamless coordination and increased performance in automated systems, this study examines the probable benefits of combining PLCs with ROS. PLCs have long been utilised in industrial settings for control and tracking jobs because they are robust and dependable. However, ROS, which was originally created for robotics, offers an extensible framework for robot control, sensing, and communication. The characteristics of both systems may be exploited to produce a synergistic effect that enhances automation capabilities and ROS integration supports data and order transfer between the two systems, allowing effective coordination and synchronisation of industrial activities. Advanced sensing and control methods in ROS may be applied by PLCs, and ROS may profit from the dependability and real-time capabilities of PLCs. This integration makes it possible for robots, sensors, and other automation components to interact easily, which improves system performance and flexibility. The mix of Robotic Operating System (ROS) and Programmable Logic Controllers (PLCs) has showed promise in improving automation effectiveness in a range of industrial uses. In order to achieve seamless coordination and increased performance in automated systems, this study examines the probable benefits of combining PLCs with ROS. PLCs have long been utilised in industrial settings for control and tracking jobs because they are robust and dependable.. © 2023 IEEE.

关键词： adaptive control complex automation system control capabilities PLC ROS

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Improving Φ-OTDR Event Classification Performance with a Semi-Supervised Model 28

Improving Φ-OTDR Event Classification Performance with a Se...

引用

28th international conference on Optical Fiber Sensors, OFS 2023

作者： Li, Yujiao Yu, Kuanglu Institute of Information Science School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing Jiaotong University Beijing100044 China

We design a semi-supervised model based on XM-ACAB for Φ-OTDR event classification. The accuracy for six types of events can reach up to 91.0% with a total of only 12 labeled samples in the experiment. © Optica ... 详细信息

ISBN: (纸本)9781957171302

关键词： Deep learning Erbium fibers Machine learning Neural networks Optical time domain reflectometry Single mode fibers

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Access the Prospect of automation in Inventory Management of Construction Projects

Access the Prospect of Automation in Inventory Management of...

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international conference on Civil Engineering Innovative Development in Engineering Advances, ICC-IDEA 2023

作者： Pavan Kumar, B. Arokiaprakash, A. Department of Civil Engineering Faculty of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Kattankulathur 603203 India

ISBN: (纸本)9789819962327

In construction industry, materials play the major role more than half of the project money is spent on the materials and managing the materials is very much needed for faster completion of project. The use of the automation techniques is still backing in the India when compared to the other countries. By proper implementing the automation in the inventory management of a construction, more time and money can be saved. In the implementation process what are the barriers and obstacles caused in the automation is discussed and also how the automation can be used in the inventory management is also discussed. Not only that and also how well the automation is being used in the present time of the construction industry also discussed. The ways to overcome the obstacles and the barriers are given. How the integrating of the technology can save the time and money is discussed in this paper. Also, how the ABC analysis technique is going to play the key role in the proper management of the inventory is given with its importance. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Construction industry

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Simulating Virtual Environment and Experience for Training, Exergaming, and Edutainment in eXtended Reality (XR): A Survey

Simulating Virtual Environment and Experience for Training, ...

引用

2023 international conference on computer Applications technology, CCAT 2023

作者： Li, Wanwan University of Tulsa Department of Computer Science TulsaOK United States

ISBN: (纸本)9798350301540

In recent years, eXtended Reality (XR) technologies, including Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR), have emerged as transformative technologies in various domains and have revolutionized the fields of training, exergaming, and edutainment. These immersive XR technologies offer unique opportunities to simulate virtual environments and experiences that facilitate interactive learning and engaging physical activities. The simulation of virtual environments and experiences plays a crucial role in delivering high-quality and effective XR programs. This survey explores existing research and advancements in simulating virtual environments and experiences for training, exergaming, and edutainment in XR. This survey aims at providing an overview of the current state of research and development, discusses the challenges and opportunities in virtual environment and experience simulation, and highlights their future directions. By clarifying the advancements in virtual environment and experience simulation, this survey helps researchers discover the potential of XR in enhancing training, promoting physical activity, and revolutionizing education. © 2023 IEEE.

关键词： Augmented reality

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Adversarial Patch Attacks Against Aerial Imagery Object Detectors Based on Interpretable Guidance

Adversarial Patch Attacks Against Aerial Imagery Object Dete...

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2023 IEEE international conference on Dependable, Autonomic and Secure Computing, 2023 international conference on Pervasive Intelligence and Computing, 2023 international conference on Cloud and Big Data Computing, 2023 international conference on Cyber science and technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2023

作者： Liu, Fengyi Lian, Zhichao School of Cyberspace Security Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9798350304602

Although image recognition and classification methods based on deep neural networks (DNNs) have accomplished remarkable achievements in the domain of computer vision, more and more research in recent years has shown that these models may have vulnerabilities that can be easily exploited by attackers, leading to incorrect output results. Especially in the realm of object detection, the incorporation of meticulously crafted patches onto images can potentially deceive DNN-based detectors, resulting in erroneous output outcomes. These patches can be carefully designed to greatly interfere with and mislead the output results of deep neural networks. These misleading output results may lead to serious security issues and losses, so it is becoming increasingly important to study and strengthen the robustness and security of DNNs based target detectors. However, previous methods did not consider the interpretability of the model, and this paper proposes a new mothed to adversarial patch attacks. First, we employ the model interpretable algorithm Grad-CAM to obtain the patch's location within the model's region of interest for the target. Subsequently, we calculate the precise patch placement and apply it accordingly. Following that, we utilize a loss function to optimize patch, ensuring its effectiveness. The experimental results obtained from the DOTA dataset indicate that our proposed method effectively degrades the performance of the target detection model. Secondly, we conducted experiments to improve the transferability of adversarial patches across different models, and verified that using patches to cover the regions of interest in the model improves the transferability of patches. © 2023 IEEE.

关键词： Deep neural networks

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An Adaptive Dynamic Service Flow Control Strategy Based on trTCM Algorithm

An Adaptive Dynamic Service Flow Control Strategy Based on t...

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2023 international conference on Intelligent Systems, Communications, and computer Networks, ISCCN 2023

作者： Yongge, Shi Yangming Yongchong, Wu GongQing Institute of Science and Technology Gongqingcheng Jiangxi332020 China Jiujiang Vocational and Technical College Jiujiang Jiangxi332007 China

ISBN: (纸本)9781510666238

When the network has burst high concurrent access traffic, the traffic allocated to each node in the cluster will exceed the maximum processing capacity of the machine, which needs to be solved by applying flow control technology. For this reason, this paper studies the flow control technology under the microservice architecture, and proposes an adaptive dynamic service flow control strategy based on the srTCM algorithm, which can dynamically regulate and differentiate the tasks entering the service node according to the request type and the running state of the machine. Experiments show that the research results of this paper are better than the common current limiting schemes. © 2023 SPIE. All rights reserved.

关键词： Concurrency control

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