One of the most common diseases in recent years has been lung cancer. In the US, around 200,000 new instances are reported annually, based on studies in this area. Malignant tumors are created when lung cells prolifer...
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Intelligent Space(IS)is widely regarded as a promising paradigm for improving quality of life through using service task *** the field matures,various state-of-the-art IS architectures have been *** of the IS architec...
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Intelligent Space(IS)is widely regarded as a promising paradigm for improving quality of life through using service task *** the field matures,various state-of-the-art IS architectures have been *** of the IS architectures designed for service robots face the problems of fixedfunction modules and low scalability when performing service *** this end,we propose a hybrid cloud service robot architecture based on a Service-Oriented Architecture(SOA).Specifically,we first use the distributed deployment of functional modules to solve the problem of high computing resource ***,the Socket communication interface layer is designed to improve the calling efficiency of the function ***,the private cloud service knowledge base and the dataset for the home environment are used to improve the robustness and success rate of the robot when performing ***,we design and deploy an interactive system based on Browser/Server(B/S)architecture,which aims to display the status of the robot in real-time as well as to expand and call the robot *** system is integrated into the private cloud framework,which provides a feasible solution for improving the quality of ***,it also fully reveals how to actively discover and provide the robot service mechanism of service tasks in the right *** results of extensive experiments show that our cloud system provides sufficient prior knowledge that can assist the robot in completing service *** is an efficient way to transmit data and reduce the computational burden on the *** using our cloud detection module,the robot system can save approximately 25% of the averageCPUusage and reduce the average detection time by 0.1 s compared to the locally deployed system,demonstrating the reliability and practicality of our proposed architecture.
Advancements in maritime satellite technology have significantly impacted the maritime industry, enhancing both communication and safety at sea. These technological improvements have enabled Automatic Identification S...
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Recent advancements in satellite technologies have resulted in the emergence of Remote Sensing (RS) images. Hence, the primary imperative research domain is designing a precise retrieval model for retrieving the most ...
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Human activity recognition involves identifying the daily living activities of an individual through the utilization of sensor attributes and intelligent learning algorithms. The identification of intricate human acti...
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The present study presents a novel approach to enhance the quality of celebrity photos by utilizing an innovative framework known as Profile SR-GAN. The aim is to increase the resolution of low-quality celebrity photo...
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Heart diseases, collectively known as cardiovascular diseases (CVDs), remain one of the foremost health challenges across the globe, taking millions of lives each year. This study evaluates the effectiveness of Multil...
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Generative AI models for music and the arts in general are increasingly complex and hard to *** field of ex-plainable AI(XAI)seeks to make complex and opaque AI models such as neural networks more understandable to **...
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Generative AI models for music and the arts in general are increasingly complex and hard to *** field of ex-plainable AI(XAI)seeks to make complex and opaque AI models such as neural networks more understandable to *** ap-proach to making generative AI models more understandable is to impose a small number of semantically meaningful attributes on gen-erative AI *** paper contributes a systematic examination of the impact that different combinations of variational auto-en-coder models(measureVAE and adversarialVAE),configurations of latent space in the AI model(from 4 to 256 latent dimensions),and training datasets(Irish folk,Turkish folk,classical,and pop)have on music generation performance when 2 or 4 meaningful musical at-tributes are imposed on the generative *** date,there have been no systematic comparisons of such models at this level of com-binatorial *** findings show that measureVAE has better reconstruction performance than adversarialVAE which has better musical attribute *** demonstrate that measureVAE was able to generate music across music genres with inter-pretable musical dimensions of control,and performs best with low complexity music such as pop and *** recommend that a 32 or 64 latent dimensional space is optimal for 4 regularised dimensions when using measureVAE to generate music across *** res-ults are the first detailed comparisons of configurations of state-of-the-art generative AI models for music and can be used to help select and configure AI models,musical features,and datasets for more understandable generation of music.
One form of energy security, as stated in Government Regulation No. 79/2014 is a condition where there is energy availability, and the energy can be reached by all levels of society. The use of Diesel Power Plants (PL...
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With more multi-modal data available for visual classification tasks,human action recognition has become an increasingly attractive ***,one of the main challenges is to effectively extract complementary features from ...
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With more multi-modal data available for visual classification tasks,human action recognition has become an increasingly attractive ***,one of the main challenges is to effectively extract complementary features from different modalities for action *** this work,a novel multimodal supervised learning framework based on convolution neural networks(Conv Nets)is proposed to facilitate extracting the compensation features from different modalities for human action *** on information aggregation mechanism and deep Conv Nets,our recognition framework represents spatial-temporal information from the base modalities by a designed frame difference aggregation spatial-temporal module(FDA-STM),that the networks bridges information from skeleton data through a multimodal supervised compensation block(SCB)to supervise the extraction of compensation *** evaluate the proposed recognition framework on three human action datasets,including NTU RGB+D 60,NTU RGB+D 120,and *** results demonstrate that our model with FDA-STM and SCB achieves the state-of-the-art recognition performance on three benchmark datasets.
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