Titlebook: Sentimental Analysis and Deep Learning; Proceedings of ICSAD Subarna Shakya,Valentina Emilia Balas,Ke-Lin Du Conference proceedings 2022 Th

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SentiSeries: A Trilogy of Customer Reviews, Sentiment Analysis and Time Series,w consumers feel about the goods and services provided by retail companies. The focus of this research is on analyzing sentiment in reviews aligned with the time series analysis that unveils quite interesting and decisive insights. The trends in user behavior, count frequency and sentiments are used

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Video Summarization Using Fully Convolutional Residual Dense Network,horter and compendious summary of the original input video without losing the contextual semantics of the same. Previous work has shown that extracting rich contextual information from the input video frames is imperative for generating summary that is closer to human interpretation of the original

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QMCDS: Quantum Memory for Cloud Data Storage,n demand services. On the other hand, quantum computing is also gaining increasing research attention due to its enormous computational power. The future will soon be defined by the combined capabilities of both technologies. The challenges of cloud computing like threats to confidentiality, integri

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A Deep Learning Approach to Analyze the Propagation of Pandemic in America,to extract important information from continuously generated data to detect and predict the COVID-19 epidemic growth by continuously monitoring it. Together with the next-generation fog computing (FC) framework, the strategies could be designed to help and manage the spread of the virus in a specifi

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Graph Convolution-Based Joint Learning of Rumor with Content, User Credibility, Propagation Context. Rumor detection task necessitates joint learning as factors such as credibility of the user, propagation and dispersion context on the social graph, and rumor content are equally significant. A bidirectional graph convolution-based approach is a feasible implementation of joint learning strategy.

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Deep Learning-Based Real-Time Object Classification and Recognition Using Supervised Learning Appro also allows them to perform various functions such as autonomous thinking ability, understanding skills, and problem-solving. Moreover, machine learning [ML] plays an important role in developing the image-processing models and application. In real-time applications, the labels of objects may be un