检索结果-内蒙古大学图书馆

Advanced CNN Architectures for Improved Garbage Image Classification: An In-depth Evaluation

Advanced CNN Architectures for Improved Garbage Image Classi...

South Eastern European Design Automation, computer engineering, computer Networks and Social Media Conference (SEEDA-CECNSM)

作者： Athanasios Kanavos Orestis Papadimitriou Gerasimos Vonitsanos Manolis Maragoudakis Phivos Mylonas Department of Information and Communication Systems Engineering University of the Aegean Samos Greece Computer Engineering and Informatics Department University of Patras Patras Greece Department of Informatics Ionian University Corfu Greece Department of Informatics and Computer Engineering University of West Attica Athens Greece

ISBN: (数字)9798331504489

ISBN: (纸本)9798331504496

Convolutional Neural Networks (CNNs) have become instrumental in advancing image classification, particularly in the context of garbage image classification, a critical component for efficient waste management. This paper introduces a tailored CNN architecture that demonstrates enhanced accuracy in garbage classification tasks, even with constrained datasets. Our architecture incorporates multiple convolutional, max-pooling, and fully connected layers, with dropout regularization strategically applied to curb overfitting and improve model generalization across a varied waste image dataset. Comparative evaluations reveal that our model achieves a significant improvement in accuracy over existing CNN models. The results not only validate the robustness of our approach but also contribute valuable insights toward developing more precise and efficient systems for garbage image classification.

关键词： Waste management Accuracy Design automation Social networking (online) Instruments Europe computer architecture Robustness Convolutional neural networks Image classification

来源：评论

学校读者我要写书评

暂无评论

Performance Evaluation of IoT-Fog-Cloud System for Data Storage, Analysis and Visualisations Using Retrial Queues Approach 8th

Performance Evaluation of IoT-Fog-Cloud System for Data St...

引用

8th International Conference on Information System Design and Intelligent Applications, ISDIA 2024

作者： Qurashi, Shahazad N. Goswami, Veeena Mund, G.B. Barik, Rabindra K. Department of Health Informatics College of Public Health and Tropical Medicine Jazan University Jazan Saudi Arabia School of Computer Applications Kalinga Institute of Industrial Technology Bhubaneswar India School of Computer Engineering Kalinga Institute of Industrial Technology Bhubaneswar India

ISBN: (纸本)9789819748945

The significance of the Internet of Things (IoT) is growing in the contemporary information age due to its quick acquisition of diverse data. Both the IoT and cloud computing systems generate vast quantities of data. Fog computing, a technique that employs leveraging, is utilised to process substantial volumes of data. Subsequently, the processed data are transmitted to a cloud storage system using fog nodes. The installation of an IoT-Fog-Cloud system leads to enhancements in both latency and throughput. The primary responsibility of the fog nodes inside the IoT-Fog-Cloud system is to perform localised collection, monitoring, and storage of IoT workload and data. This function serves to enhance efficiency and availability within the system. The discussion of compliance with Quality of Service (QoS) standards constitutes the pertinent subjects and challenges that necessitate attention in fog computing. The present article employs an M/M/1 retrial queueing model and analytical methodology to assess and examine the performance of the IoT-Fog-Cloud system, thereby offering a solution to the problem at hand. The mathematical methods employed in this study enable the determination of the service arrival required to meet the QoS criteria in IoT layer. It also provides mathematical expressions for various performance metrics of the system, including the arrival rate, service rate, retrial rate, and the average waiting time for requests in the system. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Quality of service

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of Movie Recommendation Systems Using Filtering Techniques on IMDB and Rotten Tomatoes 15

Comparative Analysis of Movie Recommendation Systems Using F...

引用

15th International Conference on Information, Intelligence, Systems and Applications, IISA 2024

作者： Majhi, Santosh Kumar Sahani, Preetipadma Pradhan, Rosy Acharya, Biswaranjan Grivokostopoulou, Foteini Kanavos, Andreas Gerogiannis, Vassilis C. Department of Computer Science and Information Technology Bilaspur India Veer Surendra Sai University of Technology Department of Computer Science and Engineering Odisha Burla India Veer Surendra Sai University of Technology Department of Electrical Engineering Odisha Burla India Marwadi University Department of Computer Engineering Ai Rajkot India Computer Technology Institute and Press 'Diophantus' Patras Greece Ionian University Department of Informatics Corfu Greece University of Thessaly Department of Digital Systems Larissa Greece

ISBN: (纸本)9798350368833

Recommendation systems are pivotal in industries like entertainment, where competitiveness is intense. This study enhances movie recommendations by utilizing rich datasets from IMDB and Rotten Tomatoes, incorporating movie ratings, user profiles, audience scores, and critics' reviews. These elements were subjected to sentiment analysis to refine the data quality. We explored three filtering techniques: content-based, which analyzes movie features;collaborative, which processes user behavior patterns;and hybrid, combining both to leverage their strengths. The effectiveness of these methods was assessed using Mean Average Precision at k (MAP-k) and Root Mean Square Error (RMSE), with our results showing notable improvements in recommendation accuracy. For instance, the hybrid method achieved a MAP ©k of 0.271 and an RMSE of 0.634, indicating enhanced precision and reliability of the recommendations. These findings suggest significant potential for improving user satisfaction and retention in digital platforms, demonstrating the benefit of integrating diverse data sources and analytical techniques in recommendation systems.

关键词： Collaborative filtering

来源：评论

学校读者我要写书评

暂无评论

Eye and People Counting Using Haar Cascade and NVIDIA Jetson Nano for Ad Analysis 1

Eye and People Counting Using Haar Cascade and NVIDIA Jetson...

引用

1st International Conference on Advanced engineering and Technologies, ICONNIC 2023

作者： Wicaksana, Cakra Adipura Hidayat, Wahyu Santoso, Muhammad Iman Alfanz, Rocky Fatkhurrokhman, Mohammad Yusfia Hafid, A. University of Sultan Ageng Tirtayasa Department of Informatics Cilegon Indonesia University of Sultan Ageng Tirtayasa Department of Electrical Engineering Cilegon Indonesia Vocational Education University of Sultan Ageng Tirtayasa Department of Electrical Engineering Serang Indonesia Sebelas Maret University Department of Informatics and Computer Engineering Education Surakarta Indonesia

ISBN: (纸本)9798350306484

Eye-detection technology is used to improve the effectiveness of advertisements. This research uses a mirrorless camera, the Harr Cascade method to detect eyes and faces, and the NVIDIA Jetson Nano as a microcontroller. The results show that the system can detect with high accuracy, even with differences in distance and face accuracy, even with differences in distance and the number of people looking at the camera. camera. This system can be used to calculate the number of effective ad readers. effective advertising readership. In the three cases tested, the system had an accuracy of 91 %,97%, and 90% for calculating the number of people viewing an advertisement, as well as an accuracy of 87% for face detection. © 2023 IEEE.

关键词： Cameras

来源：评论

学校读者我要写书评

暂无评论

Detecting Abusive Activity with Enhanced Convolutional Neural Networks

Detecting Abusive Activity with Enhanced Convolutional Neura...

引用

2023 Al-Sadiq International Conference on Communication and Information Technology, AICCIT 2023

作者： Khalaf, Suadad Zaidan Shujaa, Mohamed Ibrahim Alwahhab, Ahmed Bahaaulddin A. Middle Technical University Department of Computer Techniques Engineering Baghdad Iraq Middle Technical University Technical College of Management Department of Informatics Baghdad Iraq

ISBN: (纸本)9798350341881

There is a growing reliance on surveillance systems for law enforcement and public safety purposes. Video surveillance scenarios, such as those seen in train stations, schools, and hospitals, must automatically detect hostile and suspicious behavior to avoid social, economic, and environmental harm. Human contact can now be seen using intelligent video surveillance systems. Crowds and the camera's field of view reduce the system's effectiveness as a security procedure. As a result, there is a lot of study on the many strategies for detecting violent behavior. The method of detection discussed in this study can be divided into three categories. These groups were established as a result of the classification procedures that were used. Among the categorizations is a refined CNN for using AI to identify instances of violence. Principal Component Analysis (PCA) is used to develop techniques for feature extraction and violence detection. The AIRTLab dataset was utilized to analyze models based on dataset learning for violence detection by testing the resilience of algorithms against false positives. To evaluate the proposed model's robustness against false positives, we calculated accuracy measures and utilized them to establish a baseline on the AIRTLab dataset. The study literature claims a 99.98% success rate for the suggested models, with transfer learning-based networks boasting greater generalization abilities. © 2023 IEEE.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

An effective intrusion detection system based on feature selection and regularized long short-term memory classifier

引用

Multimedia Tools and Applications 2025年 1-24页

作者： Chikkalwar, Sudha Rani Garapati, Yugandhar Department of Computer science and Engineering GITAM Deemed to be University Rudraram Hyderabad India Department of Computer science and Informatics Mahatma Gandhi University Telangana Nalgonda India

In recent days, the expansion of Internet of Things (IoT) and the quick advancement of computer system applications contribute to the current phenomenon of data growth. The field of intrusion detection has expanded considerably as a result of the need to protect networks from various attacks. Previously, security has been provided by combining conventional intrusion monitoring systems with a high number of security measures. However, the ability of combined systems to analyze enormous amounts of data has been restricted. Therefore, in this research, open-source and freely available datasets known as NSL-KDD and CSE-CIC-IDS2018 datasets are analyzed. Those datasets contain a class column that splits the attack detection into two classes (normal and anomalous) and four categories (DoS, probe, R2L, and U2R). Then, feature encoding and scaling are used for pre-processing. After that, a SelectPercentile-based feature selection algorithm is suggested to identify the numerous various intrusion attacks and choose the best features. Later, the Regularized Long Short-Term Memory (LSTM) is employed to classify the data. The result analysis verified that Regularized LSTM surpasses the existing models in the NSL-KDD based on accuracy (99.95%), false alarm rate (0.05%), attack detection rate (99.82%), and f1-measure (99.94%). While in the CSE-CIC-IDS2018 dataset, the Regularized LSTM method achieves better accuracy (99.33%), false alarm rate (0.07%), attack detection rate (99.96), and f1-measure (99.95%). © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Network intrusion

来源：评论

学校读者我要写书评

暂无评论

Wireless Edge Controller for Robot Education Using MQTT on Dobot Magician Lite 1

Wireless Edge Controller for Robot Education Using MQTT on D...

引用

1st IEEE International Symposium on Consumer Technology, ISCT 2024

作者： Prayudi, Agus Arief, Muhammad Fauzan Zainuddin, Muhammad Agus Sukaridhoto, Sritrusta Rante, Hestiasari Politeknik Elektronika Negeri Surabaya Department of Electrical Engineering Surabaya Indonesia Politeknik Elektronika Negeri Surabaya Department of Creative Multimedia Technology Surabaya Indonesia Politeknik Elektronika Negeri Surabaya Department of Informatics and Computer Engineering Surabaya Indonesia

ISBN: (纸本)9798350365191

The integration of wireless controllers in robot education has emerged as a pivotal area to enhance the learning experience and practical understanding of robotics concepts. This paper presents the implementation of a wireless controller for educational purposes using MQTT (Message Queuing Telemetry Transport) on the Dobot Magician Lite robotic platform. MQTT, a lightweight messaging protocol, facilitates efficient communication between the controller and the robot, enabling seamless interaction and control over the robot's movements and functionalities. The implementation focuses on providing a user-friendly interface and intuitive controls, allowing students and educators to easily operate the robot while exploring various educational scenarios. Leveraging MQTT's flexibility, the system offers real-time control and monitoring capabilities, fostering interactive learning experiences in robotics education. The proposed wireless controller demonstrates the feasibility and effectiveness of employing MQTT in robot education, paving the way for enhanced learning opportunities and practical applications in the field of robotics. The examination of MQTT performance across various bandwidths provides important insights into our system's abilities. At 8 Mbps, our system achieved its highest transaction speed, averaging 1.61 transactions per second with a quick average transaction time of 0.62 seconds. Transaction speeds decreased as bandwidth decreased, with 1 Mbps showing the slowest average TPS of 1.24. Importantly, data retention stayed at 100% for all bandwidths, demonstrating consistent reliability. © 2024 IEEE.

关键词： Educational robots

来源：评论

学校读者我要写书评

暂无评论

Performance estimation of direct and indirect transmission in V2X communications

Performance estimation of direct and indirect transmission i...

引用

2024 Panhellenic Conference on Electronics and Telecommunications, PACET 2024

作者： Keramidi, Irene Uzunidis, Dimitris Moscholios, Ioannis Yiannopoulos, Konstantinos Sagias, Nikos Sarigiannidis, Panagiotis University of Peloponnese Dept. Informatics and Telecommunications Tripolis Greece University of West Attica Dept. Electrical and Electronic Engineering Athens Greece University of W. Macedonia Dept. Electrical and Computer Engineering Kozani Greece

ISBN: (纸本)9798350318845

In this paper, we evaluate the performance of a vehicular ad hoc network that enables Vehicle-to-Everything (V2X) communication considering direct and indirect packet transmission. As a performance indicator, we use the blocking probability due to the unavailability of resources. For the blocking probability calculation, we utilize two loss models from the teletraffic theory. The results demonstrate that both the capacity of the V2X links and the number of hops in the multi-hop transmission significantly affect the blocking probability of a request for service and consequently the QoS. © 2024 IEEE.

关键词： Blocking probability

来源：评论

学校读者我要写书评

暂无评论

FC Portugal: RoboCup 2024 3D Simulation League Champions

FC Portugal: RoboCup 2024 3D Simulation League Champions

引用

27th RoboCup International Symposium, 2024

作者： Abreu, Miguel Mota, Pedro Azevedo, Tomás Silva, Francisco Reis, Luís Paulo Lau, Nuno Florido, Mário LIACC/LASI/FEUP Artificial Intelligence and Computer Science Lab Faculty of Engineering of the University of Port University of Porto Porto Portugal LIACC/LASI/FCUP Artificial Intelligence and Computer Science Lab Faculty of Sciences of the University of Porto University of Porto Porto Portugal IEETA/LASI/DETI Institute of Electronics and Informatics Engineering of Aveiro Department of Electronics Telecommunications and Informatics University of Aveiro Aveiro Portugal

ISBN: (纸本)9783031858581

FC Portugal, a simulated humanoid soccer team from the universities of Porto and Aveiro, achieved the third consecutive victory in the main competition of the 2024 RoboCup 3D Simulation League. The team registered 16 wins, 3 ties, and 2 losses, scoring a total of 105 goals while only conceding 17. FC Portugal also ended first in two secondary events: the Scientific Challenge, which evaluates innovative scientific contributions within the league, and the Fat Proxy Challenge, where teams share a common set of low-level skills and compete for the best high-level strategy. The codebase used in this competition was developed in Python after RoboCup 2021. This paper presents a brief overview of its structure along with the new features developed for this year’s competition. The key developments include a hierarchical learning framework, presented at the Scientific Challenge, and the release of our codebase to the RoboCup community. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： 3D modeling

来源：评论

学校读者我要写书评

暂无评论

Quantum-Based Prediction Model for Carbon Neutrality

Quantum-Based Prediction Model for Carbon Neutrality

引用

International Conference of Advanced informatics: Concept, Theory and Application (ICAICTA)

作者： Ghifari Munawar Kridanto Surendro School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Department of Computer Engineering and Informatics Politeknik Negeri Bandung Bandung Indonesia

ISBN: (数字)9798331520311

ISBN: (纸本)9798331520328

Carbon neutrality is a global target pursued by cities worldwide to achieve a balance between carbon emissions and removals, reaching a net-zero carbon state. Mitigation measures are being implemented to reduce emissions and enhance carbon sequestration, aiming to meet the targets set for 2050 or 2060. However, challenges posed by urban sprawl and increasing urbanization raise concerns about the feasibility of achieving carbon neutrality. Various studies have been conducted to project the attainment of this goal by developing prediction models. Machine learning (ML) prediction models use socio-economic, energy, and technological data to forecast carbon neutrality. These models consider factors like GDP per capita, urbanization rate, total energy consumption, and forest stock volume, formulating scenarios based on policy documents and historical data. Some models have incorporated optimization methods like the sparrow search algorithm, genetic neural network, and aquila optimizer to improve prediction accuracy. However, classical optimization methods have limitations, such as susceptibility to getting trapped in local optima, which can affect model performance. Quantum-based optimization methods, particularly quantum annealing (QA), are emerging as potential solutions to address these challenges by leveraging the principles of quantum mechanics to optimize complex problem spaces. QA enhances ML processes like feature selection, hyperparameter optimization, and regression model optimization. This study provides a review of pipeline processes from state-of-the-art methods, as well as their potential quantum-based enhancements, to achieve more precise predictive models.

关键词： Annealing Computational modeling Urban areas Quantum mechanics Optimization methods Predictive models Carbon neutral Quantum annealing Hyperparameter optimization Feature extraction

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：