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检索条件"任意字段=2021 10th International Conference on Computing and Pattern Recognition"

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Extensive Study on Color and Light Translation of 2D Images using Machine Learning Approaches 10

Extensive Study on Color and Light Translation of 2D Images ...

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10th international conference on System Modeling and Advancement in Research Trends, SMART 2021

作者： Labh, Jyoti Ranjan Dwivedi, R.K. TMU College of Computing ScienceampInformation Technology Department Computer Application Moradabad India

ISBN: (纸本)9781665439701

For machine learning applications, digital image production provides for the efficient generation of huge volumes of training data while preserving control over the generation process to ensure the optimal content distribution and variation. Synthetic data has the potential to become an important element of the training pipeline as the demand for deep learning applications grows. Over the last decade, a broad range of strategies for producing training data have been presented. the collecting of these for comparison and categorization is required for future improvement. this study presents a complete list of available visual machine learning image synthesis approaches. In the context of 2D picture production, these are classed as light transfer and colour transfer. the focus is on the computational features of approaches for developing machine learning colour transfer between image-to-image translation in the future. Finally, the learning potential of each approach is assessed based on its reported quality and performance. the study is meant to serve as a complete reference for both data and application developers. this is a comprehensive list of all the methods and approaches discussed in this page. © 2021 IEEE.

关键词： Color

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Predicting Diabetes using CNN for Various Activation Functions: A Comparative Study 10

Predicting Diabetes using CNN for Various Activation Functio...

引用

10th international conference on System Modeling and Advancement in Research Trends, SMART 2021

作者： Goel, Sofia Sharma, Sudhansh Tripathi, R.C. Indira Gandhi National Open University SOCIS New Delhi India TMU Faculty of Engineering and Computing Sciences UP Moradabad India

ISBN: (纸本)9781665439701

Diabetes mellitus is a chronic disease that produces blood glucose abnormalities. this needs to be monitored at regular intervals. Many machine learning models made significant contribution in the prediction of diabetes. One such deep learning model is the convolution neural network. It is a multi-layered network architecture that comprises convolution, pooling, output layers, and activation functions. Activation functions are used to learn and approximate the relationships between various features in the model for final output. this research paper focus on comparing the performance of the CNN model using four non-linear activation functions;sigmoid, tanh, ReLU, ELU for blood glucose prediction. the model uses a simglucose UVA/Padova dataset of 30 patients for experimental analysis. Additionally, the model presents a three-class classification problem, where the patient is classified as euglycemic, hypoglycaemic, and hyperglycaemic. Statistical measures like recall, precision, F-score, and accuracy are used to assess the performance of CNNs employing various activation functions. the experimental results show that CNN gives the maximum accuracy of 97.3% when applied with the ELU activation function. © 2021 IEEE.

关键词： Forecasting

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Realizing Algorithms Using GUI 10

Realizing Algorithms Using GUI

引用

10th international conference on System Modeling and Advancement in Research Trends, SMART 2021

作者： Jain, Amit Chandigarh University University Institute of Computing Punjab Mohali India

ISBN: (纸本)9781665439701

In modern times, the use of Visual assistance including mixed media makes contributions undoubtedly in order to didactic fee of in-magnificence and e-learning based schooling. In this paper, a visualization device has been tested to mark its impact at the ratings and with aid of implication, the information tiers inside data structures path have been *** of handling the core subject like Data Structure and Algorithms constitutes a vital basis of subject matter in technological era but so many college graduates fail to understand it properly as because of the huge and complex number of principles and hypothesis. Hence, the expectation is that the software shall help all users including college graduates or higher, to recognize the knowledge of code and pseudo codes referring to sorting *** is an interactive on-line platform that presents graphical view of algorithms from code [2]. In this paper, set of rules related to sorting represents how the detail in an array are taken care of and this envision allows the human mind to recognize the unique sorting algorithms in preference to going through the lengthy codes. this is a computer software;therefore, individual can effectively use it and research the sorting set of rules and examine the principles on every situation. the modern-day software is applied for illustration of array factors, sorting of factors and controlling the velocity of sorting the factors along with the dimensions of array. © 2021 IEEE.

关键词： Data structures

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Enabling Pervasive Federated Learning using Vehicular Virtual Edge Servers

Enabling Pervasive Federated Learning using Vehicular Virtua...

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19th IEEE international conference on Pervasive computing and Communications (IEEE PerCom)

作者： Du, Anran Shen, Yicheng Tseng, Lewis Higuchi, Takamasa Ucar, Seyhan Altintas, Onur Boston Coll Boston MA 02215 USA Toyota Motor North Amer R&D InfoTech Labs Mountain View CA USA

ISBN: (纸本)9781665404242

Recent works have proposed various distributed federated learning (FL) systems for the edge computing paradigm. these FL algorithms can assist pervasive applications in various aspects, e.g., decision making, pattern recognition, and behavior prediction. Existing solutions do not efficiently support the training based on the real-time location-specific data, because fundamentally, the "data collection" problem is rarely studied in the context of FL systems. To address this problem, we present a novel system, VC-SGD (Vehicular Clouds-Stochastic Gradient Descent), which seamlessly integrates the emerging concept of vehicular clouds with an edge-based FL. We show that by using vehicular clouds as virtual edge servers, VC-SGD is able to effectively support FL algorithms that use real-time location-specific data. We develop a general simulator that uses SUMO to simulate vehicle mobility and MXNet to perform real training. We use our simulator to verify the efficacy of VC-SGD. the experimental results demonstrate that VC-SGD improves over existing solutions.

关键词： Federated Learning Machine Learning Edge computing Vehicular Clouds Simulation

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Application of computing Platform in Cloud computing 10th

Application of Computing Platform in Cloud Computing

引用

10th international conference on Frontier computing, FC 2020

作者： Zhuo, Yue Department of Architectural Engineering Zhengzhou Technical College Zhengzhou450121 China

ISBN: (纸本)9789811601149

With the development of computer network technology, network education has emerged. the traditional physical education has a strong practicality, which is an interactive activity between teachers and students. At the same time, physical education teaching also has a strong demonstration and imitation. Based on these characteristics, the application of multimedia network teaching in physical education is inevitable. the multimedia network teaching has broken through the traditional physical education teaching mode and has supplemented the traditional physical education teaching insufficiency. © 2021, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Sports

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HM-QCNN: Hybrid Multi-branches Quantum-Classical Neural Network for Image Classification 9th

HM-QCNN: Hybrid Multi-branches Quantum-Classical Neural Netw...

引用

19th international conference on Advanced Data Mining and Applications, ADMA 2023

作者： Liu, Haowen Gao, Yufei Shi, Lei Wei, Lin Shan, Zheng Zhao, Bo School of Cyber Science and Engineering Songshan Laboratory Zhengzhou University Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9783031466632

Quantum machine learning has been developing in recent years, demonstrating great potential in various research domains and promising applications for pattern recognition. However, due to the constraints of quantum hardware, the input qubits are restricted caused by small circuit size, and the fuzziness in all dimensions caused by the features that are difficult to be effectively mined. Besides, previous studies focus on binary classification, but multi-classification received little attention. To address the difficulty in multi-classification, this paper proposed a hybrid multi-branches quantum-classical neural network (HM-QCNN) that utilizes a multi-branch strategy to construct the convolutional part. the part consists of three branches to extract the features of different scales and morphologies. Two quantum convolutional layers apply quantum CRZ gates and rotational gates to design a random quantum circuit (RQC) with 4 qubits and full qubits measurements. the experiments on three public datasets (MNIST, Fashion MNIST, and MedMNIST) demonstrate that HM-QCNN outperforms other prevalent methods with accuracy, precision, and convergence speed. Compared with the classical CNN and the hybrid neural network without multi-branches, HM-QCNN reached 97.40% and improved the accuracy of classification by 6.45% and 1.36% on the MNIST dataset, respectively. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Qubits

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A Coarse-to-Fine Framework for Head and Neck Tumor Segmentation in CT and PET Images 1

引用

2nd 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2021, held in conjunction with 24th international conference on Medical Image computing and Computer-Assisted Intervention, MICCAI 2021

作者： An, Chengyang Chen, Huai Wang, Lisheng Department of Automation Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai200240 China

ISBN: (数字)9783030982539

ISBN: (纸本)9783030982522

Radiomics analysis can help patients suffered from head and neck (H&N) cancer customize tailoring treatments. It requires a large number of segmentation of the H&N tumor area in PET and CT images. However, the cost of manual segmentation is extremely high. In this paper, we propose a coarse-to-fine framework to segment the H&N tumor automatically in FluoroDeoxyGlucose (FDG)-Positron Emission Tomography (PET) and Computed Tomography (CT) images. Specifically, we trained three 3D-UNets with residual blocks to make coarse stage, fine stage and refined stage predictions respectively. Experiments show that such a training framework can improve the segmentation quality step by step. We evaluated our framework with Dice Similarity Coefficient (DSC) and Hausdorff Distance at 95% (HD95) of 0.7733 and 3.0882 respectively in the task 1 of the HEad and neCK TumOR segmentation and outcome prediction in PET/CT images (HECKTOR2021) Challenge and ranked second. © 2022, Springer Nature Switzerland AG.

关键词： Positron emission tomography

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Classification of Histology Images Based on a Compact 3D Representation 1

引用

15th international conference on pattern recognition and Information Processing, PRIP 2021

作者： Brancati, Nadia Cicala, Crispino Frucci, Maria Riccio, Daniel Institute for High Performance Computing and Networking National Research Council of Italy Naples Italy Computer Scientist Milan Italy University "Federico II" Naples Italy

ISBN: (数字)9783030988838

ISBN: (纸本)9783030988821

Although the Convolutional Neural Networks (CNNs) have been widely adopted for the classification of histopathology images, one of the main drawbacks of CNNs is their inability to cope with gigapixel images. To deal with the high resolution of Whole Slide Image (WSI), many methods focus on patch processing which can result in improper representation if the patches are analyzed independently, losing the context information that is fundamental in digital pathology. In this study, the WSI is mapped into a compressed representation preserving the topological and morphological information relating to spatial correlations of neighboring patch features of the WSI. Such a representation is used to train a CNN to solve a classification task of breast histological images. the effectiveness of the suggested framework is demonstrated through experiments on Camelyon16 dataset. the results show the performance of our approach when three different ways to incorporate the spatial correlation in the tensor are used singly or in combination, highlighting that it is comparable with the state of the art. © 2022, Springer Nature Switzerland AG.

关键词： Image classification

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Solving Complex Intersection Management Problems Using Bi-level MINLPs and Piecewise Linearization Techniques 10th

Solving Complex Intersection Management Problems Using Bi-le...

引用

10th international conference on Smart Cities and Green ICT Systems, SMARTGREENS 2021, and 7th international conference on Vehicle Technology and Intelligent Transport Systems, VEHITS 2021

作者： Gerdts, Matthias Rogovs, Sergejs Valenti, Giammarco Department of Aerospace Engineering Institute of Applied Mathematics and Scientific Computing Universität der Bundeswehr München Neubiberg Germany Department of Industrial Engineering University of Trento Trento Italy

ISBN: (纸本)9783031170973

We investigate a complex Intersection Management Problem (IMP) for automated vehicles and introduce a method for the automated coordination of vehicles with the aim to minimize total clearance time for the intersection. the method is capable of handling multiple vehicles (per lane or distributed over several lanes), multiple lanes, variable arrival times and velocities, and multiple turn options in non-symmetric intersection scenarios. In order to optimally coordinate the vehicles we employ a bi-level optimization formulation coupling a scheduling problem at the upper level with an optimal control problem at the lower level. the latter takes into account the dynamics of the vehicles and the former aims to find an optimal sequence of arrivals at the intersection. Collision avoidance on the complete driving paths, i.e., at, before and after the intersection, is ensured by the problem formulation. In order to solve the resulting mixed-integer nonlinear bi-level optimization problem we develop suitable piecewise linearization techniques for the value function of the optimal control problems which eventually yields a large-scale mixed-integer linear problem. Numerical examples show the efficiency of the proposed approach. © 2022, Springer Nature Switzerland AG.

关键词： Vehicles

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Study on Cluster-Based pattern recognition Using Recommendation System 2nd

Study on Cluster-Based Pattern Recognition Using Recommendat...

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2nd international conference on Communication, Networks and computing, CNC 2020

作者： Chaurasia, Shailendra Shrivastava, Prashant Kamble, Megha Chouksey, Bhanupriya Computer Science Department LNCT Excellence Bhopal Bhopal India

ISBN: (纸本)9789811688959

the recommendations system has growing relevance to internet service and overload of information is one of the most critical incidents that users meet on the Internet. To make suggestions based on similar interests between users or items, Recommender Systems uses collective filtering. Clusters shall classify population or data points so that data points in the same category are more comparable to other data points in the same category and differ from data points in other categories. pattern detection and matching include parameters such as average, correlation, and mutual information, etc. the PR can be used as a classification method for extracting and grouping patterns into various groups. PR is a classification method. PR is an intermediary process. In this review, we researched data mining, Clustering, Recommendation systems, pattern recognition, and described different types of recommendation systems as well as defined various methods of clustering & pattern recognition. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Recommender systems

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