检索结果-内蒙古大学图书馆

An Efficient USE-Net Deep Learning Model for Cancer Detection

International Journal of Intelligent Systems 2023年第1期2023卷

作者： Almutairi, Saad M. Manimurugan, S. Aborokbah, Majed M. Narmatha, C. Ganesan, Subramaniam Karthikeyan, P. Industrial Innovation & Robotics Center Faculty of Computers and Information Technology University of Tabuk Tabuk71491 Saudi Arabia Department of Electrical and Computer Engineering Oakland University Rochester112345 United States Department of Computer Science and Information Engineering National Chung Cheng University Chiayi Taiwan

Breast cancer (BrCa) is the most common disease in women worldwide. Classifying the BrCa image is extremely important for fnding BrCa at an earlier stage and monitoring BrCa during treatment. Te computer-aided detection methods have been used to interpret BrCa and improve the detection of BrCa during the screening and treatment stages. However, if a new BrCa image is generated for the treatment, it will not classify correctly. Te main objective of this research is to classify the BrCa images for newly generated images. Te model performs preprocessing, segmentation, feature extraction, and classifcation. In preprocessing, a hybrid median fltering (HMF) is used to eliminate the noise in the images. Te contrast of the images is enhanced using quadrant dynamic histogram equalization (QDHE). Ten, ROI segmentation is performed using the USE-Net deep learning model. Te CafeNet model is used for feature extraction on the segmented images, and fnally, classifcation is made using the improved random forest (IRF) with extreme gradient boosting (XGB). Te model obtained 97.87% accuracy, 98.45% sensitivity, 95.24% specifcity, 98.96% precision, and 98.70% f1-score for ultrasound images. Te model gives 98.31% accuracy, 99.29% sensitivity, 90.20% specifcity, 98.82% precision, and 99.05% f1-score for mammogram images. © 2023 John Wiley and Sons Ltd. All rights reserved.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Modified Elite Opposition-Based Artificial Hummingbird Algorithm for Designing FOPID Controlled Cruise Control System

引用

Intelligent Automation & Soft Computing 2023年第11期38卷 169-183页

作者： Laith Abualigah Serdar Ekinci Davut Izci Raed Abu Zitar Computer Science Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl al-Bayt UniversityMafraq25113Jordan Department of Electrical and Computer Engineering Lebanese American UniversityByblos13-5053Lebanon Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman19328Jordan Applied Science Research Center Applied Science Private UniversityAmman11931Jordan School of Computer Sciences Universiti Sains MalaysiaPulau Pinang11800Malaysia School of Engineering and Technology Sunway University MalaysiaPetaling Jaya27500Malaysia Department of Computer Engineering Batman UniversityBatman72100Turkey MEU Research Unit Middle East UniversityAmmanJordan Sorbonne Center of Artificial Intelligence Sorbonne University-Abu DhabiAbu DhabiUnited Arab Emirates

Efficient speed controllers for dynamic driving tasks in autonomous vehicles are crucial for ensuring safety and *** study proposes a novel approach for designing a fractional order proportional-integral-derivative(FOPID)controller that utilizes a modified elite opposition-based artificial hummingbird algorithm(m-AHA)for optimal parameter *** approach outperforms existing optimization techniques on benchmark functions,and we demonstrate its effectiveness in controlling cruise control systems with increased flexibility and *** study contributes to the advancement of autonomous vehicle technology by introducing a novel and efficient method for FOPID controller design that can enhance the driving experience while ensuring safety and *** highlight the significance of our findings by demonstrating how our approach can improve the performance,safety,and reliability of autonomous *** study’s contributions are particularly relevant in the context of the growing demand for autonomous vehicles and the need for advanced control techniques to ensure their safe *** research provides a promising avenue for further research and development in this area.

关键词： Cruise control system FOPID controller artificial hummingbird algorithm elite opposition-based learning

来源：评论

学校读者我要写书评

暂无评论

Recent and Future Innovative Artificial Intelligence Services and Fields 4

Recent and Future Innovative Artificial Intelligence Service...

引用

4th International Symposium on Agents, Multi-Agents Systems and Robotics, ISAMSR 2021

作者： Jawad, Mohammed Saeed Mahdin, Hairulnizam Mohammed Alduais, Nayef Abdulwahab Hlayel, Mohammed Mostafa, Salama A. Abd Wahab, Mohd Helmy Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Johor Malaysia Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia Johor Malaysia

ISBN: (纸本)9781728166544

Recent innovative Artificial Intelligence (AI) solutions accelerate digital transformations in different fields. It is important to highlight and explore this innovative AI service in different domains so that digital transformation can be planned, designed, and implemented for maximum society benefits. This paper investigates the different fields of AI services that can be utilized towards achieving highly beneficial digital transformations in different societal domains. This includes marketing, finance and banking, healthcare industry, emotion, and creative AI, as well as recent AI fields as explainable and responsible AI. Exploring and understanding the innovative AI services in these domains widen researcher capabilities to achieve effective and highly beneficial digital transformations. © 2021 IEEE.

关键词： Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Adaptive Modeling for Real-Time Data Analysis with Machine Learning

Adaptive Modeling for Real-Time Data Analysis with Machine L...

引用

Smart Generation Computing, Communication and Networking (SMART GENCON), International Conference on

作者： Mahesh TR Shweta Singh Vaibhav Srivastav Hitesh Kalra T. Surulivel rajan Gitanjali B. Yadav Computer Science and Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bangalore Karnataka India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Department of Computer Science & Engineering Vivekananda Global University Jaipur India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and technology Chitkara University Punjab India Department of Mechanical Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai Department of Artificial Intelligence & Data Science Vishwakarma Institute of Information Technology Pune India

Adaptive Modeling for actual-Time information evaluation with system studying is a critical studies area in the modern-day technology of information-in depth evaluation. Conventional gadget studying strategies are static, meaning that the models do no longer evolve as information scientist interactions occur or because the data changes over time. As a result, models can grow to be obsolete and further downstream machine overall performance will become constrained. Consequently, the want for adaptive modeling algorithms has arisen with the intention to permit dynamic, system-stage getting to know from statistics. Such strategies look to provide affordable predictions for real-time inputs, while also looking forward to enough destiny reaction behavior to make more accurate predictions for destiny, unseen facts. The purpose of this approach is to create a solution which optimally balances accuracy and flexibility for an ever converting environment. One of these system could be carried out for predictive upkeep, diagnostic analysis, cyber security detection or self-sustaining vehicle decision making.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Predicting of Uncertainty Facial Expressions in Children with Autism Spectrum Disorder Based on an Improved Fuzzy Convolutional Neural Network Model

SSRN

引用

SSRN 2024年

作者： Abd-Alhalem, Samia M. Ali, Hesham A. El-Shafai, Walid Algarni, Abeer D. Soliman, Naglaa F. El-Samie, Fathi E. Faculty of Artificial Intelligence Delta University for Science and Technology Gamasa35712 Egypt Computers and Control Systems Engineering Department Faculty of Engineering Mansoura University Mansoura35516 Egypt Security Engineering Lab Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia Zagazig University Egypt Menoufia University Egypt

Facial expression recognition plays a pivotal role in comprehending emotions and social interactions, particularly in individuals grappling with autism spectrum disorder (ASD), who often encounter challenges in non-verbal communication. For some with ASD, even subtle shifts in their facial expressions can prove elusive, rendering it arduous to categorize their emotional states accurately. Consequently, the analysis and processing of facial expression data hold the potential to facilitate early autism diagnosis, thereby enabling timely therapeutic interventions and alleviating the economic and psychological burdens experienced by patients. In this study, we introduce an enhanced approach that leverages a fuzzy convolutional neural network (CNN) and an Improved Binary Genetic Algorithm (IBGA) for autism diagnosis based on facial expression data. Our model confronts the intricate task of recognizing facial images by selecting salient features employing the IBGA method. Moreover, it employs fuzzy weights to ascertain the probability of similarity within the classifier layer. Our proposed model has yielded impressive outcomes, boasting an average accuracy of 0.9405 for ASD detection and 0.9365 for the recognition of six distinct facial expressions. These results hold profound implications for the enhancement of emotion recognition systems and the refinement of interventions aimed at bolstering social interactions for individuals grappling with ASD. © 2024, The Authors. All rights reserved.

关键词： Emotion Recognition

来源：评论

学校读者我要写书评

暂无评论

Time-Aware Missing Traffic Flow Prediction for Sensors with Privacy-Preservation 11th

Time-Aware Missing Traffic Flow Prediction for Sensors with ...

引用

11th International Conference on computer engineering and Networks, CENet2021

作者： Qi, Lianyong Wang, Fan Xu, Xiaolong Dou, Wanchun Zhang, Xuyun Khosravi, Mohammad R. Zhou, Xiaokang School of Computer Science Qufu Normal University Qufu China School of Computer and Software Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science and Technology Nanjing China State Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University Nanjing China Department of Computing Macquarie University SydneyNSW2109 Australia Department of Computer Engineering Persian Gulf University Bushehr Iran Department of Electrical and Electronic Engineering Shiraz University of Technology Shiraz Iran Faculty of Data Science Shiga University Hikone Japan

ISBN: (纸本)9789811665530

With the continuous development of IoT, a number of sensors establish on the roadside to monitor traffic conditions in real time. The continuously traffic data generated by these sensors makes traffic management feasible. However, loss of data may occur due to inevitable sensor failure, impeding traffic managers to understand traffic dynamics clearly. In this situation, it is becoming a necessity to predict missing traffic flow accurately for effective traffic management. Furthermore, the traffic sensor data are often distributed and stored by different agencies, which inhibits the multi-party sensor data sharing significantly due to privacy concerns. Therefore, it has become a major obstacle to balance the tradeoff between data sharing and vehicle privacy. In light of these challenges, we propose a privacy-aware and accurate missing traffic flow prediction approach based on time-aware Locality-Sensitive Hashing technique. At last, we deploy a set of experiments based on a real traffic dataset. Experimental reports demonstrate the feasibility of our proposal in terms of traffic flow prediction accuracy and efficiency while guaranteeing sensor data privacy. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Data privacy

来源：评论

学校读者我要写书评

暂无评论

Investigating and Implementing the Efficiency of Image Restoration Techniques in Digital Image Processing

Investigating and Implementing the Efficiency of Image Resto...

引用

Smart Generation Computing, Communication and Networking (SMART GENCON), International Conference on

作者： Kalyan Acharjya S. Yuvaraj Varsha D. Jadhav Amritpal Sidhu Deepak Kumar Sinha Ojasvee Kaneria Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Department of Electronics and Communication Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai Department of Artificial Intelligence & Data Science Vishwakarma Institute of Information Technology Pune INDIA Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and technology Chitkara University Punjab India Computer Science and Engineering Faculty of Engineering and Technology Bangalore Karnataka India Department of Computer Science & Engineering Vivekananda Global University Jaipur India

This look at explores the efficiency of diverse photo recovery strategies, inclusive of noise reduction, histogram change, facet enhancement, polishing, and smoothing, in digital picture processing. An extensive evaluation of the techniques becomes conducted to assess their effectiveness in restoring degraded virtual pictures. Numerous objective metrics, together with Structural Similarity (SSIM) Index, peak sign-to-Noise Ratio (PSNR), and mean Squared blunders (MSE), have been used to quantitatively examine the first-rate of the restored photographs. Effects indicated that noise discount and area enhancement furnished the finest improvements within the snap shots. Histogram changes and sprucing also stepped forward the high-quality of the pictures, at the same time as the smoothing technique ended in a moderate lower in pleasant. This examines offers a detailed insight into the efficiency of various photo healing techniques and can serve as a reference for in addition investigations.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Application of Adaptive Modulation Strategies for Enhancing Peak Bit Rates in High-Speed Fiber Optic Communication Networks

Application of Adaptive Modulation Strategies for Enhancing ...

引用

Smart Generation Computing, Communication and Networking (SMART GENCON), International Conference on

作者： Pravin R. Futane Rakesh Kumar Yadav Saniya Khurana Amar Shankar Abhijeet Kar V. Ashok Department of Information Technology Vishwakarma Institute of Information Technology Pune India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and technology Chitkara University Punjab India Food Technology Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bangalore Karnataka India Department of Computer Science & Engineering Vivekananda Global University Jaipur India Department of Mechanical Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai

Optical communication networks suffer from excessive peak bit quotes today's the physical and environmental constraints present day fiber optic cables. Adaptive modulation techniques offer a potential approach to the trouble with the aid of making an allowance for increased facts throughput with the aid of tailoring the information rate latest the signal to the channel's country. Those techniques have the ability to modify modulation formats and facts fees in real-time to optimize the height bit fee and universal throughput modern the network. This paper examines the software trendy adaptive modulation strategies for enhancing top bit prices in excessive-velocity fiber optic verbal exchange networks and evaluations the to be had strategies for fixing this hassle. The evaluation additionally critiques the present day adaptive modulation algorithms and their overall performance in terms modern-day top bit fee and throughput modern-day the verbal exchange networks. Finally, this paper affords an overview modern day several future research challenges important for further improvements in this discipline.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Implementing Long Short-Term Memory Network for Enhancing Hyper Spectral Time Series Modeling

Implementing Long Short-Term Memory Network for Enhancing Hy...

引用

Paradigm Shift in information Technologies with Innovative Applications in Global Scenario (ICPSITIAGS), IEEE International Conference on

作者： Muktha Eti Jyoti Shekhawat Manish Nagpal Srisainath R Pranali G. Chavhan Rakesh Kumar Yadav Department of Electrical and Electronics Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bangalore Karnataka India Department of Computer Science & Application Vivekananda Global University Jaipur India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and technology Chitkara University Punjab India Department of Mechanical Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai-127 Department of Computer Engineering Vishwakarma Institute of Information Technology Pune India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (数字)9798350329773

ISBN: (纸本)9798350329780

This take a look at proposes using lengthy quick-time period reminiscence (LSTM) networks as a tool for enhancing the accuracy of Hyper Spectral Time series (HSTS) fashions. via the use of this recurrent neural community approach, the model can account for the temporal dating among the hyper spectral spectral time collection variables. additionally, with this utility, the version can research from the spectral time series over a longer time period. This study examined the efficacy of the carried out LSTM network with the aid of comparing the results to the Hyper Spectral Time collection model performance performed prior to using this method. The effects recommend that the addition of the LSTM network accelerated the accuracy of the version through about 25%. This generation has the potential to substantially beautify the accuracy of temporal records inside the discipline of faraway sensing records analysis. In conclusion, this examine indicates that LSTM networks are a promising tool for boosting the predictive energy of HSTS models. long quick-term memory Networks (LSTM) are a type of Recurrent Neural Networks (RNNs) that have been applied to many duties in synthetic Intelligence including language information, herbal language processing, and image processing. more recently, they had been used to enhance hyper spectral time series modeling. The shape of LSTM permits it cope with and keep lengthy-term sequences of statistics, making it particularly suitable for modeling hyper-spectral time series. At whenever step, an LSTM community takes as input a vector representing the hyper-spectral values, and outputs a vector which represents the intermediate representation of the time series. these intermediate representations are then used to generate the output at every next time step. LSTM networks are for his or her ability to capture lengthy-time period dependencies, and because of their structure, they are additionally nicely-appropriate to hyper-spectral time collecti

关键词： Performance evaluation Recurrent neural networks Shape Time series analysis Predictive models Vectors Robustness

来源：评论

学校读者我要写书评

暂无评论

Age-Optimal Computation Offloading for Mobile Edge Computing System

Age-Optimal Computation Offloading for Mobile Edge Computing...

引用

IEEE International Conference on Communications Workshops, ICC

作者： Yi Chen Zheng Chang Geyong Min School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Faculty of Information Technology University of Jyväskylä Jyväskylä Finland Department of Computer Science University of Exeter Exeter U.K.

Numerous Internet of Things (IoT) applications are sensitive to the freshness of status information for accurate monitoring and control. Due to the limitation of computational resources, status updates of IoT devices can be offloaded to the mobile edge computing (MEC) server for execution to enhance the information freshness. In this work, we investigate the computation offloading problem in the MEC-assisted IoT. Age of processing (AoP), which takes the data processing time into account, is adopted as a performance metric to measure the freshness of the information of IoT devices. To achieve the age-optimal solution, we explicitly consider the heterogeneity of the status information and develop the offloading decision with both linear and non-linear age functions. An average AoP minimization problem is then formulated as a decentralized computation offloading game and we propose an age-optimal computation offloading mechanism to obtain the optimal offloading strategy. Simulation results show the convergence of our proposed method and demonstrate the effectiveness of the proposed scheme under different scenarios.

关键词：

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：