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检索条件"任意字段=9th International Conference on Computer Aided Design and Computer Graphics"

共 9679 条记录，以下是1091-1100 订阅

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YOLOv8 Detection Head Improvements for FPGA Deployments

YOLOv8 Detection Head Improvements for FPGA Deployments

引用

6th international conference on Intelligent Computing and Signal Processing (ICSP)

作者： Zihan Guan Bingrui Liu Min Xie Zehuan Yang School of Integrated Circuits and Electronics Beijing Institute of Technology Beijing China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

Object detection is a core topic in the field of computer vision, which is widely used in industrial quality inspection, video surveillance, UAV target recognition and other scenes. these applications require extremely high speed of object detection. However, the existing advanced object detection networks often face computational bottlenecks. In order to solve this problem, this paper proposes a FPGA-based YOLOv8 target detection network data sharing detection head. By introducing a shared data module into the decoupling head, the design not only effectively reduces the amount of network computation, but also improves the application value of target detection technology, and opens up new possibilities for FPGA in high performance computing.

关键词： computer vision Target recognition High performance computing Face recognition Object detection Signal processing Inspection Video surveillance Autonomous aerial vehicles Field programmable gate arrays

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Analysis and design of computer Networks to Analyze Traffic Flow by Utilizing a Network Monitoring System

Analysis and Design of Computer Networks to Analyze Traffic ...

引用

international conference on Business and Industrial Research (ICBIR)

作者： Tio Adistiyawan Sarwo Yulius Denny Prabowo Jullend Gatc Eko Cahyo Nugroho Computer Science Department BinusOnline Universitas Bina Nusantara Jakarta Indonesia

ISBN: (数字)9798350383027

ISBN: (纸本)9798350383034

this research discusses the analysis and design of computer networks, which aim to reduce traffic problems in network infrastructure. this research uses NDLC as a methodology by utilizing the Network Monitoring System to analyze and monitor network performance. NMS is used to collect network traffic data, analyze traffic patterns, identify the causes of problems, and provide solutions to optimize traffic flow. this paper examines the existing network infrastructure at PT TD Automotive Compressor Indonesia, including network topology, network devices used, and network configuration and settings. Next, a more efficient and optimal network design is carried out to overcome the identified traffic problems. the data collection method used in this research involves collecting data through observation, interviews, literature study, and network performance measurement. the collected data is then analyzed using appropriate techniques and tools, including NMS. the results of this paper can also provide recommendations and solutions that PT TD Automotive Compressor Indonesia can implement to improve network efficiency and performance and reduce traffic problems. thus, this paper is essential to computer network management and traffic flow optimization.

关键词： Performance evaluation Companies Telecommunication traffic Traffic control Real-time systems Problem-solving Monitoring Optimization Automotive engineering Business

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Automated Detection of Multi-type Small Lesions in CT Images Based on Deep Learning

Automated Detection of Multi-type Small Lesions in CT Images...

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international conference on Image, Vision and Computing (ICIVC)

作者： Shuhua Li Mary Jane C. Samonte Fenglong Yan School of Information Technology Mapua University Manila Philippines School of Computer Science and Technology Guangdong University of Science and Technology Dongguan China School of Computer & Software Dalian Neusoft University of Information Dalian China

ISBN: (数字)9798350385991

ISBN: (纸本)9798350386004

With the rapid development of deep learning, the medical image analysis method has become one of the most concerned issues in the field of medical imaging diagnosis. Medical image analysis and processing are essential for effective treatment and excellent prognosis of medical lesions. In this paper, High-definition computed tomography (CT) images of multi-type lesions are analyzed. To solve the problem of insufficient medical images, Mosaic is used within DeepLesion database for data combination and enhancement. In addition, images from COVIDCT are incorporated into the dataset. Concerning data noise, different kinds of filtering methods are tested and noise removal is performed using non-local mean filtering. Based on deep separable convolution (DSC), the accuracy of the training network is improved by using the enhanced dataset. the experimental results show that the average accuracy of the model is 80.5% at 29.23 frames per second, which satisfies the real-time detection. It provides a feasibility study for the practical application of computer-aided diagnosis.

关键词： Training Accuracy Image analysis Filtering Computed tomography Noise Real-time systems Lesions Labeling Medical diagnostic imaging

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An Investigation into Student Performance Prediction using Regularized Logistic Regression

An Investigation into Student Performance Prediction using R...

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international conference on Computing, Engineering, and design (ICCED)

作者： Felix Indra Kurniadi Meta Amalya Dewi Dina Fitria Murad Sucianna Ghadati Rabiha Awanis Romli Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia Faculty of Computing Universiti Malaysia Pahang Pahang Malaysia

the problem of university dropout poses a significant challenge to education systems worldwide, affecting administrators, teachers, and students. Early identification and intervention strategies are crucial for addressing this issue. In addition, advances in machine learning have paved the way for more accurate predictions of student performance. this paper investigates the use of regularization techniques, specifically Lasso (L1) and Ridge (L2) regularization, within logistic regression models to improve the accuracy of performance prediction. this research’s dataset was obtained from the Binus Online Learning platform at Bina Nusantara University, with a focus on the Information System study program between 2020 and 2021. the results reveal that logistic regression with regularization achieves a high level of accuracy, recall, and precision in predicting student performance. the findings contribute to the development of an early warning system to identify at-risk students, enabling timely intervention and support.

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A design of Longitudinal and Lateral Controllers for Autonomous Driving System in Carla Simulator

A Design of Longitudinal and Lateral Controllers for Autonom...

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international conference on Robotics and Automation Engineering (ICRAE)

作者： Fengchen Wei Weiji Wang Hanwen Liu Dept. Engineering and Design University of Sussex Brighton UK SPRU University of Sussex Brighton UK

ISBN: (数字)9798331518301

ISBN: (纸本)9798331518318

Research on the design of autonomous vehicle controllers has always been the focus and difficulty in the field of autonomous driving. However, with the rapid development of artificial intelligence technology and the continuous revolutionary achievements in natural language processing and computer vision, more and more autonomous driving researchers have focused their research on the perception field of autonomous vehicles and ignored the research on controllers. Even if there are some studies on controllers, they only focus on lateral control or longitudinal control, and there are few comprehensive considerations of lateral and longitudinal vehicle controller designs. Our work makes up for this deficiency. First, we selected different controller designs for the vehicle’s lateral and longitudinal control, respectively, and conducted hundreds of simulation experiments under the same scenario, speed, and trajectory planning algorithm to obtain lateral and longitudinal controller design solutions suitable for specific scenarios; second, we compared different autonomous driving simulation platforms and finally chose Carla as our simulation platform.

关键词： computer vision Trajectory planning Neural networks Natural language processing Artificial intelligence Robotics and automation Autonomous vehicles Testing

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Emotion Recognition from Facial Expression Using Deep Learning Techniques

Emotion Recognition from Facial Expression Using Deep Learni...

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international conference for Convergence of Technology (I2CT)

作者： Prateek Mishra Abhishek Singh Verma Pratyush Chaudhary Aamit Dutta Computer Science Engineering Sharda University Greater Noida India

ISBN: (数字)9798350394474

ISBN: (纸本)9798350394481

Emotion recognition from facial expressions stands as a pivotal challenge in computer vision and human-computer interaction. In this study, we explore the area and base our research on the robust FER2013 dataset. Our main goal is to investigate the efficiency of deep learning methods in this situation, specifically using the CNN, VGG16, and VGG19 architectures. We carefully evaluate the effectiveness of these deep learning models in identifying and categorizing emotions from facial photos through extensive experimentation and review. Our results show that the VGG19 design obtained a remarkable accuracy rate of 92.5%. this result represents a significant advancement in the capacity of automated emotion recognition systems. this research emphasizes the value of utilizing cutting-edge deep learning architectures and dataset resources in the quest for more precise and effective emotion recognition from facial expressions, with potential applications ranging from mental health assessment to human-computer interaction.

关键词： Deep learning Emotion recognition Technological innovation Reviews Navigation Neural networks Mental health

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Development of a Method for Automatic Extraction of Ontology Entity Names from Natural Language Texts

Development of a Method for Automatic Extraction of Ontology...

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international conference on computer Science and Engineering (UBMK)

作者： Sadirmekova Zhanna Elmira Daiyrbayeva Karbozova Indira Bekbolatov Samat M. Kh. Dulaty Taraz Regional University Taraz Kazakhstan Inst. of Information and Computational Technologies of the Committee of Science of the Ministry of Science and Higher Educ. of the Rep. of Kazakhstan Almaty Kazakhstan Satbayev University Almaty Kazakhstan International Taraz Innovation Institute named after Sh. Murtaza Taraz Kazakhstan

ISBN: (数字)9798350365887

ISBN: (纸本)9798350365894

Domain ontologies play a crucial role in organizing, sharing, and reusing domain-specific knowledge within software systems. However, developing a software ontology is a time-consuming and complex process. To create such an ontology, a large number of relevant publications must be analyzed. this task of enriching the ontology with data from these sources can be streamlined and accelerated through the use of lexical and syntactic patterns derived from ontological design. this paper presents a method for the automated construction of ontologies within a scientific domain, leveraging a system of heterogeneous ontological design patterns (ODPs). this system includes ODPs tailored for ontology developers and automatically generated lexical and syntactic patterns, which can be used to enrich ontologies with information extracted from natural language texts.

关键词： Knowledge engineering computer science Systematics Natural languages Ontologies Syntactics Software systems Feature extraction Data mining

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Service Oriented Fuzzy Decision Model for Road Traffic Engineering

Service Oriented Fuzzy Decision Model for Road Traffic Engin...

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international conference on Computing, Engineering, and design (ICCED)

作者： Ditdit Nugeraha Utama Fauzan Affan Zaki Intan Juliani Munjeri Nidya Utami Putri Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia Information Systems Department UIN Syarif Hidayatullah Jakarta Indonesia

A number of attempts have already been implemented formally to solve road traffic congestion. However, the objective strategy type of road traffic engineering could not be proven truly. Try and error is one inefficient way in road traffic engineering to degrade the level of congestion. the study was conducted to propose a new service-oriented model (SOM) that combines fuzzy-logic and water flow algorithm methods (called FWFA). the method combination was operated as the main method to construct the decision model for selecting the objective strategy in road traffic engineering. Also, service-oriented architecture (SOA) is realized to implement such a constructed model practically. the Model can suggest the most optimal strategy decision in road traffic engineering. Here, a main traffic road of Juanda in area Ciputat, Tangerang Selatan, province Banten, Indonesia; was selected as a research object in this study. the constructed SOM for road traffic engineering was structurally delivered in this paper.

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design and Evaluation of IoT Gateway for Data Prioritization based on Van Emde Boas Tree 9

Design and Evaluation of IoT Gateway for Data Prioritization...

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9th international conference on Future Internet of things and Cloud, FiCloud 2022

作者： Araujo, Ingrid Palma De Araujo, Ronaldo C. R. Ribeiro, Michel Alves Ishikawa, Edison Reis, Ana C. B. Rodopoulos, Christiano A. M. Department of Computer Science Brasilia Brazil

ISBN: (数字)9781665493505

ISBN: (纸本)9781665493505

Critical data can require actions immediate (rate appropriate to the context) as well as priority in routing the device to the Cloud. In this sense, one of the contributions of this work is to show that the prioritization of packets originating from IoT devices, which travel between Local Gateway and Cloud Gateway, via HTTPS protocols, using data structures such as Heap (Fibonacci and Binominal) and Van Emde Ems (vEB tree) are more effective than commonly used FIFO queues. Another contribution of this work is the adaptation of the mentioned data structures to the IoT. the results showed the huge advantage of vEB tree over Heaps implemented primarily in a context with the large quantity of data. © 2022 IEEE.

关键词： Data structures

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Systems design Concepts Mimicking Bio-inspired Self-assembly 9th

Systems Design Concepts Mimicking Bio-inspired Self-assembly

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9th international conference on Research into design, ICoRD 2023

作者： Sanjay, Sarma O. V. Ardoin, Cameron Ibrahim, Israr M. Parasuraman, Ramviyas Pidaparti, Ramana M. College of Engineering University of Georgia AthensGA30605 United States North Oconee High School BogartGA30622 United States Department of Mechanical Engineering Universitas Syiah Kuala Aceh23111 Indonesia Department of Computer Science University of Georgia AthensGA30605 United States

ISBN: (纸本)9789819904273

design of complex self-assembly systems requires intelligent solutions that can be manufactured effectively and efficiently. Self-organization is the spontaneous formation of organized structures that can dynamically reconfigure with changing environments. these processes are primarily observed in chemical and biological processes that resemble large-scale ecosystems and in environments as small as biological cells. Inspired by these natural processes, there is also a growing research interest in developing 4D design and printing technologies in which 3D structures reconfigure with changing stimuli. the 4D design process requires appropriate design, computational, and simulation tools aimed at building structures at larger scales that can augment the current engineering design and manufacturing processes. this study presents a new multi-agent framework with two new paradigms called agents-as-blocks and free-agent. We present further details on these new strategies in the form of preliminary case studies applied to simulating micro-environments of microtubules’ self-organization process and through a vibration simulation platform. Our simulation results closely follow the real formation patterns in the microtubules process and show some interesting self-organizing and self-assembling patterns that change with varying geometries, rules, and stimuli in a vibration platform environment. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Self assembly

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