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检索条件"任意字段=Proceedings of the 2023 12th International Conference on Computing and Pattern Recognition"

共 696 条记录，以下是281-290 订阅

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Audio Deepfake Detection Using Deep Learning 12

Audio Deepfake Detection Using Deep Learning

引用

12th international conference on System Modeling and Advancement in Research Trends, SMART 2023

作者： Anagha, R. Arya, A. Narayan, V. Hari Abhishek, S. Anjali, T. Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Amritapuri India

ISBN: (纸本)9798350369861

the capacity to identify real audio recordings from their modified counterparts is essential in the age of sophisticated digital manipulation for maintaining security and trust in a vari- ety of applications, from media forensics to voice authentication systems. this research aims to create a deep learning model that can distinguish between authentic and altered audio files, with an emphasis on identifying audio deepfakes. the study uses Mel spectrogram representations and data augmentation techniques to effectively extract features from the ASV spoof 2019 dataset and train models. Convolutional neural networks (CNNs) comprising a number of layers, including convolutional, pooling, batch normalization, ReLU activation, dropout, global average pooling, and a dense classification layer are used as the foundation of the design. the Adam optimizer is used to optimize the model once it has been trained using binary cross-entropy loss, and a variety of metrics, such as accuracy, F1 score, ROC curve, and AUC, are used to track its performance. By making it easier to identify audio deepfakes, this project will ultimately increase the security and integrity of audio data in the digital world. © 2023 IEEE.

关键词： Feature extraction

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A Quality Control Model for Lung Cancer Based on A Standardized Treatment Mode 12

A Quality Control Model for Lung Cancer Based on A Standardi...

引用

12th international conference of Information and Communication Technology, ICTech 2023

作者： Dong, LiYing Wang, Ning Zhao, Kui Ma, Ming Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang110168 China University of Chinese Academy of Sciences Beijing100049 China General Hospital of Northern Theater Command Shenyang China

ISBN: (纸本)9798350332919

In the medical field, quality of care is one of the most important goals, and only by achieving good quality of care can we provide better health services to the society. therefore, it is particularly important to implement quality control of the diagnosis and treatment process. In this paper, we propose a lung cancer quality control model based on the standardized judgment of the treatment model to address the requirements of lung cancer treatment quality control, the complex content of medical text data, and the irregular recording time. First, the word vector is trained by BERT pre-training model;then, the K-medoids algorithm is used to mine the standardized treatment patterns, and the time-aware LSTM unit is used to deal with the uneven input interval on this basis;finally, the attention mechanism is introduced to highlight the different contributions of the visit days to complete the prediction of the next cycle of lung cancer treatment items. the experimental results showed that the recall and average accuracy of the BERT-TLSTM-ATT fusion model reached 0.895 and 0.782, respectively, which performed well compared with other models and effectively controlled the quality of next-cycle treatment, achieving the goal of quality control of all aspects of lung cancer treatment. © 2023 IEEE.

关键词： Quality control

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Incorporating intensity edges in the recovery of occlusion regions

Incorporating intensity edges in the recovery of occlusion r...

引用

international conference on pattern recognition

作者： S.S. Intille A.F. Bobick Perceptual Computing Group Media Laboratory MIT Cambridge MA USA

A method for incorporating intensity edge information into the recovery of occlusion regions using a pixel-based stereo algorithm is presented. the authors review the construction of disparity space images and their use to solve the stereo occlusion problem. the authors show the relationship between intensity edges and the disparity space images, and extend their stereo technique to use information about intensity discontinuities at occlusion edges. the combination of ground control points and edge information yields excellent occlusion regions.

关键词： Image analysis Laboratories Spatial coherence Pixel Image segmentation Layout Lighting Integrated circuit testing Humans Shape

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A Data Driven Digital Twin Visualization Method for Motion Control 12

A Data Driven Digital Twin Visualization Method for Motion C...

引用

12th international conference of Information and Communication Technology, ICTech 2023

作者： Liu, Guotai Sun, Na Yu, Dong Shenyang Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Shenyang China The 703 Research Institute of Cssc Harbin China

ISBN: (纸本)9798350332919

Aiming at the interaction and fusion of digital space and physical space in digital twin system, a data driven digital twin visualization method for motion control is proposed. OPC UA protocol is adopted to realize data acquisition, and the disconnection reconnection mechanism is added to deal with emergencies;the acquisition time frequency is determined to ensure the smooth movement of the twin model, and the real-time data persistence operation is realized to facilitate the inverse time analysis of historical data;Realize the motion constraint of the twin model, add the parent-child hierarchical relationship between the motion limit constraint and the components of the equipment model, ensure that the twin model conforms to the real physical properties, and realize the motion drive, including coordinate movement, rotation, clamping, etc;the reverse time replication service is realized by adding data smoothing and other functions. the feasibility of the method is verified on the NC machine tool test bed and the stacking robot, which provides a practical basis for the method. © 2023 IEEE.

关键词： Visualization

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Inversion and Prediction of Carbon Emissions Based on Remote Sensing Data and BP-XGBoost Model 12

Inversion and Prediction of Carbon Emissions Based on Remote...

引用

12th international conference of Information and Communication Technology, ICTech 2023

作者： Wang, Guodong Wang, Ning Zhou, Xiaolei Qiu, Yan Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China The Open University of Deyang Deyang China

ISBN: (纸本)9798350332919

In this paper, we first use the BP model optimized by particle swarm optimization (PSO) to integrate DMSP-OLS nighttime light data and NPP-VIIRS nighttime light data to establish a long-time series of nighttime light data sets were obtained. And using the integrated nighttime light data, temperature data and geographical data, based on the Bayesian optimization algorithm (BO) optimized XGBoost model, a carbon dioxide emission prediction model was constructed. In this study, the dataset based on nighttime light data shows a significant positive correlation to carbon emissions. As a result, the dataset can be used to estimate carbon emissions. And when using the BO-XGBoost model to invert carbon emissions, the R2 is 0.9791, and the RMSE is 29.9118, which is the most accurate predictive outcome compared to other models. the results of this study will help simplify the work of carbon emission accounting and provide an important basis for regional carbon emission policies. © 2023 IEEE.

关键词： Forecasting

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Website Traffic Time Series Forecasting Using Regression Machine Learning 12

Website Traffic Time Series Forecasting Using Regression Mac...

引用

12th IEEE international conference on Communication Systems and Network Technologies, CSNT 2023

作者： Sikka, Dhruv Vinoth Kumar, C.N.S. Srm Institute of Science and Technology School of Computing College of Engineering and Technology Department of Networking and Communications Kattankulathur603203 India

ISBN: (纸本)9781665462617

the term ''Web analytics'' pertains to the act of monitoring, analysing, and creating reports regarding the use of a website, such as its web pages, images, and videos. By utilising web analytics, businesses can retain their customers, increase their website traffic, and attract more visitors, which ultimately leads to higher revenue. A study has been conducted on statistical forecasting teaching notes of a website, which involved analysing five years of daily time series data for various traffic measures. these measures included the daily counts of page views, unique visitors, first-time visitors, and returning visitors for academic teaching notes on the website. this work presents a single unit of multiple regression machine learning models that can predict new user and returning user web traffic amounts over some time that can be expected over a certain period or on a specific time interval. the voting Regression model combines algorithms like Decision Tree Regression, Multi Linear Regression and Support Vector Machine Regression into a single unit that can predict expected traffic volume over a period with 99.96% accuracy and 0.24% of absolute error. © 2023 IEEE.

关键词： Websites

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An Open Framework for Nonverbal Communication in Human-Robot Interaction 15th

An Open Framework for Nonverbal Communication in Human-Robot...

引用

15th international conference on Ubiquitous computing and Ambient Intelligence

作者： Lozano, Ernesto A. Sanchez-Torres, Carlos E. Lopez-Nava, Irvin H. Favela, Jesus CICESE Comp Sci Carretera Ensenada Tijuana Ensenada 22860 Baja California Mexico UABC Comp Sci Km 106Carretera Tijuana Ensenada Ensenada 22860 Baja California Mexico

ISBN: (纸本)9783031486418;9783031486425

Nonverbal communication plays a vital role in human interaction. In the context of Human-Robot Interaction (HRI), social robots are designed primarily for verbal-based communication with humans, making nonverbal communication an open research area. We present a flexible, open framework designed to facilitate nonverbal interactions in HRI. Among its components is a P2P Browse-rBased Computational Notebook, leveraged to code, run, and share reactive programs. Machine-learning models can be included for real-time recognition of gestures, poses, and moods, employing protocols such as MQTT. Another key component is a broker for distributing data among different physical devices like the robot, wearables, and environmental sensors. We demonstrate this framework's utility through two interaction scenarios: (i) the first one employing proxemics and gaze direction to initiate an impromptu encounter, and (ii) a second one incorporating object recognition and a Large-Language Model to suggest meals to be cooked based on available ingredients. these scenarios illustrate how the framework's components can be seamlessly integrated to address new scenarios, where robots need to infer nonverbal cues from users.

关键词： Human-Robot Interaction Nonverbal communication Broker architectural pattern Langchain ChatGPT Computational Notebook

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Towards a Proactive System of DDoS Attacks Detection in the Cloud 12th

Towards a Proactive System of DDoS Attacks Detection in the ...

引用

12th international conference on Soft computing and pattern recognition, SoCPaR 2020 and 16th international conference on Information Assurance and Security, IAS 2020

作者： Ouhssini, Mohamed Afdel, Karim Agherrabi, Elhafed LabSIV Department of Computer Science Faculty of Science Ibn Zohr University Agadir Morocco LabIRF-SIC Department of Mathematics Faculty of Science Ibn Zohr University Agadir Morocco

ISBN: (纸本)9783030736880

Nowadays, cloud computing becoming a vital technology for organization and users by providing services through the internet. Flexibility, Efficiency, high scalability, and cost effective are the main advantages of cloud computing. However, cloud computing still suffers against attacks that threat its availability, especially DDoS attacks. this type of attack makes service unavailable by sending a huge number of flows generated by different distributed devices. High false positive rate, high time detection and high computing cost are the main challenges of exiting system of attack detection in the cloud. In this paper, we present new approach to detect DDoS attack in the cloud based on time series analysis and machine learning techniques. Statistical methods and deep learning are used to forecast the number of normal flows in the next minute, if the number of received flows is far exceeded the forecasted number, a preprocessing process is trigged followed by classifier to differ between DDoS attack and normal flows. Our system is evaluated by using public dataset CIDDS-001 and satisfactory results obtained an accuracy of an accuracy of 100%, a f1-score of 99.96% and a time detection of 0.29 s. © 2021, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cloud computing

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A cooperative integration of stereopsis and optic flow computation

A cooperative integration of stereopsis and optic flow compu...

引用

international conference on pattern recognition

作者： G. Sudhir S. Banerjee K.K. Biswas R. Bahl Centre for Applied Research in Electronics Indian Institute of Technology New Delhi India Department Computer Science and Engineering Indian Institute of Technology New Delhi India

A cooperative integration of stereopsis and optic flow computation is presented. Central to our approach is the modelling of the visual processes as a sequence of coupled Markov random fields by defining suitable interprocess interactions based on some natural constraints. the integration makes each of the individual processes better constrained and more reliable. Further, as a result of the integration, it becomes possible to accurately preserve the discontinuities in both the flow and the disparity fields along with the regions of stereo occlusion. Some results, both on noisy synthetic image data and real images are presented.

关键词： Optical computing Integrated optics Image motion analysis Network address translation Optical noise Data flow computing Image sequences Computer science Physics computing

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Ant Colony Optimization for Resource Allocation in Cloud computing Environments 12

Ant Colony Optimization for Resource Allocation in Cloud Com...

引用

12th IEEE international conference on Intelligent Data Acquisition and Advanced computing Systems: Technology and Applications, IDAACS 2023

作者： Kniazhyk, Taras Muliarevych, Oleksandr Lviv Polytechnic National University Lviv79013 Ukraine

ISBN: (纸本)9798350358056

this article delves into cloud computing technologies, addressing the challenges and concerns that arise in this domain, specifically focusing on resource allocation. We investigate and compare three optimization algorithms - Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Genetic Algorithm (GA) - in the context of their applications, objectives, and mechanisms of action. Additionally, the article highlights the significance of each algorithm in optimizing cloud resources and discusses their advantages and drawbacks. For cloud computing with higher complexity, it becomes increasingly important to develop efficient strategies for managing and allocating resources, which in turn helps organizations control costs and improve performance. Prepared comparative analysis aims to provide a comprehensive understanding of the three algorithms, equipping decision-makers with the knowledge to select the most suitable optimization method for their specific cloud computing needs and challenges. © 2023 IEEE.

关键词： ACo cloud computing Ga Psa resource allocation

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