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检索条件"任意字段=4th International Conference on Optimization Learning Algorithms and Applications"

共 13703 条记录，以下是551-560 订阅

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Design and Development of Attendance System Using Face Recognition 4

Design and Development of Attendance System Using Face Recog...

引用

4th international conference on Soft Computing for Security applications, ICSCSA 2024

作者： Krishna, Abhay Manoj, Nandana Subbulakshmi, T. Vellore Institute of Technology Bachelor in Computer Science Chennai India Vellore Institute of Technology Chennai India

ISBN: (纸本)9798331515720

the face identification technology-based attendance system represented in this paper is a novel design. the new system is an alternative to conventional more reliable, secure, and user-friendly. methods the key components are a robust face detection and recognition algorithm, a database management system, and an intuitive interface. the system achieves high accuracy, scalability, and privacy compliance by utilizing machine learning. the real-Time performance testing results show that it can be successfully used in various scenarios, thus becoming a significant breakthrough in the automated attendance management system. © 2024 IEEE.

关键词： attendance system educational institutions face detection machine learning web-based

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Adversarial Detection of Android Malicious applications Based on Feature Decentralization 4

Adversarial Detection of Android Malicious Applications Base...

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4th international conference on Blockchain Technology and Information Security, ICBCTIS 2024

作者： Qiang, Gao State Grid Jining Power Supply Company Shandong Jining272000 China

ISBN: (纸本)9798331528324

Machine learning-based methods for detecting malicious Android applications are widely researched, but their security is a concern. Adversarial attacks can easily evade the detection of these methods. this paper designs a feature-dispersion-based Android malware detection method that can effectively defend against adversarial attacks. the method takes the function call graph as features and reduces the feature dimensions according to the function types. the feature matrix is then separated to form 349 features of 1*349 dimensions, while 349 lightweight convolutional neural networks are used for malicious application detection. Experimental results on public datasets show that the method in this paper is effective in detecting adversarial attacks, with a high detection rate of 94.83%. © 2024 IEEE.

关键词： Adversarial machine learning

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A Cost Efficient Reversible QCA Multiplexer for Low Power applications 4

A Cost Efficient Reversible QCA Multiplexer for Low Power Ap...

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4th international conference on Artificial Intelligence and Signal Processing

作者： Aruna, Patthi Komanapalli, Gurumurthy VIT AP Univ Sch Elect Engn Amaravati Andhra Pradesh India

ISBN: (纸本)9798350350661;9798350350654

Low-power architectures are increasingly significant across a spectrum of applications, ranging from the Internet of things (IoT) and Quantum Computing. the Quantum dot cellular automata (QCA) is regarded as a promising platform for implementing digital circuits at the nanoscale owing to its less power consumption (PC) and great performance. the proposed design is a 4x1 multiplexer (MUX) using QCA technology. the MUX serves as a fundamental building block in digital systems, enabling the selection of one out of four input signals based on a control signal. Our proposed design leverages the unique properties of QCA, such as Coulombic interactions among quantum dots, to realize compact and efficient multiplexing functionality. We present a Controlled Operational Gate(COG) with detailed design methodology, layout optimization techniques, and performance analysis of the proposed 4x1 QCA 4x1 MUX using COG. Simulation results demonstrate the feasibility and effectiveness of our design in terms of area efficiency, latency, and quantum cost leading to low PC. the proposed 4x1 QCA MUX holds promise for realizing complex digital systems with improved performance and energy efficiency, paving the way for advanced nanoscale computing applications.

关键词： Quantum electronics QCA power consumption nanoscale computing reversibility

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optimization of weight update for convolutional operators for domestic accelerators 5

Optimization of weight update for convolutional operators fo...

引用

5th international conference on Computer Engineering and Application (ICCEA)

作者： Wang, Xibing Chen, Yongqing Lie, Bin Bu, Jingde Zhengzhou Univ Sch Comp & Artificial Intelligence Zhengzhou Peoples R China Dawning Informat Ind Beijing Co Ltd Beijing Peoples R China

ISBN: (纸本)9798350386783;9798350386776

Convolutional neural networks play an important role in deep learning, which includes three processes: forward propagation, backpropagation, and weight update. On domestic heterogeneous accelerators, the performance of the weight update operator is somewhat weak. In this paper, we handwritten and optimized the weight update operator on domestic heterogeneous accelerators, including both ordinary convolution and grouped convolution. Among them, ordinary convolution uses the implicit gemm algorithm, Grouped convolution uses a parallelized direct convolution algorithm, which reduces memory usage and has strong universality. Parallel direct convolution algorithms make better use of it.

关键词： Operator optimization weight updates convolutional neural networks Domestic accelerators

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Blood Smear morphological analysis and optimization through machine learning model 4

Blood Smear morphological analysis and optimization through ...

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4th international conference on Advancement in Electronics and Communication Engineering, AECE 2024

作者： Soni, Palvi Tandan, Gajendra Kalinga University Department of Cs & It Raipur India

ISBN: (纸本)9798350364729

this article examines the utility of image processing and machine learning in analyzing the shape and structure of cell pictures obtained from peripheral blood smears, particularly on automatic identification. the fundamental principles of the three primary components (segmentation, quantitative characteristics, and classification) are delineated, and contemporary works are examined. this study examines malignant lymphoids and normal cells. these technologies can assist cytologists in conducting practical, objective, and rapid morphological studies of blood cells. they can help analyze specific morphological characteristics and function as educational and research instruments. Further study is required to establish screening strategies that effectively utilize image-based automated recognition systems in testing facilities, alongside other analysis approaches, as part of their regular operations. © 2024 IEEE.

关键词： Machine learning

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the optimization of parameters for a Circulation loss accident classification model 4

The optimization of parameters for a Circulation loss accide...

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4th international conference on Advanced algorithms and Signal Image Processing, AASIP 2024

作者： Wang, Qi Mu, Xiangyang Li, Hengfeng Zhang, Jiahao School of Electronic Engineering Xi’an Shiyou University Xi’an710065 China Xi'an ESWIN Material Technology Co. Ltd. Xi’an710065 China

ISBN: (数字)9781510682818

ISBN: (纸本)9781510682801

Mud leakage poses a persistent challenge in drilling operations, necessitating innovative solutions for improved sealing and circulation efficiency. this paper leverages data from the Mullen Field to categorize mud loss severity levels. Employing the Optuna framework, hyperparameter optimization enhances model performance metrics such as precision, recall, and F1-score. Our study underscores the efficacy of hyperparameter tuning in refining predictive models for mud loss severity. © 2024 SPIE.

关键词： Mathematical optimization Performance modeling Machine learning Decision trees Random forests Data modeling Safety Engineering Lawrencium Statistical modeling

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Advanced Analog Design optimization: Comparison between Reinforcement learning and Heuristic algorithms 20

Advanced Analog Design Optimization: Comparison between Rein...

引用

20th international conference on Synthesis, Modeling, Analysis and Simulation Methods and applications to Circuit Design, SMACD 2024

作者： Chevalier, Michel Trochut, Severin Guizzetti, Roberto Urard, Pascal Labrak, Lioua Samuel, John Cellier, Rémy Abouchi, Nacer STMicroelectronics Crolles France Université de Lyon CPE Lyon Institut des Nanotechnologies de Lyon Lyon France Université de Lyon CPE Lyon LIRIS Lyon France

ISBN: (纸本)9798350351927

Last decades have seen a lot of research on Analog Design Automation. the most recent approaches are based on Reinforcement learning (RL). this paper describes a new learning strategy enhancing the most recent Proximal Policy optimization RL approach, applied to analog design. the method is compared to more classical heuristic approaches such as Ant Colony optimization, Particle Swarm optimization or Differential Evolution algorithm. this study is done using a gymnasium environment embedding a spice-like electrical simulator. the experiments are done under equivalent calculation conditions. the paper highlights convergence properties and demonstrates the RL ability to avoid local minimum traps. © 2024 IEEE.

关键词： Reinforcement learning

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Self-supervised representation learning for histopathological images using contrastive learning 4th

Self-supervised representation learning for histopathologica...

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4th international conference on Computational Methods in Science and Technology, ICCMST 2024

作者： Gupta, Ekta Gupta, Varun Chandigarh College of Engineering and Technology Punjab University Chandigarh India

ISBN: (纸本)9781032911571

Artificial Intelligence (AI) is becoming popular in the field of histopathological imaging. there isn’t a lot of annotated medical image data, and it is time consuming task to get this data annotated. the self-supervised learning (SSL) is an upcoming approach used for the unlabelled data. this paper suggests an SSL-based approach to classify breast cancer histopathological images. Self-supervised contrastive learning is used to learn the representations from unlabelled datasets and then used the same representations for the classification tasks of histopathological images of the labelled datasets. Two publically aavailable breast cancer datasets are used in the proposed approach: BreakHis and BCHD. Our method obtained an accuracy of 95.96% for the BreakHis dataset and 91.4% for the BCHD dataset. these results show that self-supervised learning can help learn representations of images, even if there isn’t labelled data and also this approach can help to make AI models work better in medical imaging applications. © 2025 the Author(s).

关键词： Self-supervised learning

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Creating Sorted Grid Layouts with Gradient-based optimization 24

Creating Sorted Grid Layouts with Gradient-based Optimizatio...

引用

4th Annual international conference on Multimedia Retrieval (ICMR)

作者： Barthel, Kai Uwe Barthel, Florian Tim Eisert, Peter Hezel, Nico Schall, Konstantin HTW Berlin Visual Comp Grp Berlin Germany Fraunhofer HHI Berlin Germany HU Berlin Berlin Germany

ISBN: (纸本)9798400706028

Visually sorted grid layouts provide an efficient method for organizing high-dimensional vectors in two-dimensional space by aligning spatial proximity with similarity relationships. this approach facilitates the effective sorting of diverse elements ranging from data points to images, and enables the simultaneous visualization of a significant number of elements. However, sorting data on two-dimensional grids is a challenge due to its high complexity. Even for a small 8-by-8 grid with 64 elements, the number of possible arrangements exceeds 1.3.10(89) - more than the number of atoms in the universe - making brute-force solutions impractical. Although various methods have been proposed to address the challenge of determining sorted grid layouts, none have investigated the potential of gradient-based optimization. In this paper, we present a novel method for grid-based sorting that exploits gradient optimization for the first time. We introduce a novel loss function that balances two opposing goals: ensuring the generation of a "valid" permutation matrix, and optimizing the arrangement on the grid to reflect the similarity between vectors, inspired by metrics that assess the quality of sorted grids. While learning-based approaches are inherently computationally complex, our method shows promising results in generating sorted grid layouts with superior sorting quality compared to existing techniques.

关键词： Visual Image Exploration Sorted Grid Layouts Permutation learning Quadratic Assignment Problem

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Evaluation of Heuristic optimization algorithms for Model Predictive Ventilation Control and Reducing Energy Consumption 9th

Evaluation of Heuristic Optimization Algorithms for Model Pr...

引用

9th international Building Physics conference

作者： Bielenda, Ryan Tariku, Fitsum BCIT Bldg Sci Ctr Excellence Burnaby BC V5G 3H2 Canada Now Stantec Morrison Hershfield Burnaby BC V5C 6S7 Canada

ISBN: (纸本)9789819783199;9789819783175;9789819783168

Research shows that heuristic optimization algorithms can find solutions for complex problems in the physical world. Pairing these algorithms with machine learning models for predictive building control applications has been widely explored. this study investigates the efficacy of determining optimal ventilation rates using a particle swarm optimization (PSO) algorithm, a genetic algorithm (GA), and a hybridized genetic particle swarm optimization (GPSO) algorithm developed using MATLAB within an EnergyPlus building energy simulation model. Weather data from Vancouver is used to exemplify a marine climate, where free-cooling opportunities are relatively abundant. the algorithm performance results are collected for both the heating and cooling seasons and are compared against each other for run times, energy savings, and indoor air quality performance. the results are compared against simulation results using a conventional demand control ventilation (DCV) system. Results indicate that when compared to the DCV controller with an economizer mode, heuristic optimization control methods are capable of reducing HVAC energy consumption during a cooling season with free-cooling opportunities by up to 14.1%. Additionally, all three optimization algorithms are capable of minimizing HVAC energy consumption with zero unmet hours for the indoor carbon dioxide concentration setpoint.

关键词： Particle Swarm optimization Genetic Algorithm Predictive Control Ventilation Rates Free-Cooling Artificial Neural Networks Marine Climate Energy Efficiency Indoor Air Quality

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