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Praveen Kumar Reddy Maddikunta

Bio: Praveen Kumar Reddy Maddikunta is an academic researcher from VIT University. The author has contributed to research in topics: Deep learning & Artificial neural network. The author has an hindex of 11, co-authored 36 publications receiving 409 citations.

Papers
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Journal ArticleDOI
TL;DR: This paper aims to provide a survey-based tutorial on potential applications and supporting technologies of Industry 5.0 from the perspective of different industry practitioners and researchers.

314 citations

Journal ArticleDOI
TL;DR: An overview of deep learning and its applications to healthcare found in the last decade is provided and three use cases in China, Korea, and Canada are presented to show deep learning applications for COVID-19 medical image processing.

282 citations

Journal ArticleDOI
TL;DR: This article has proposed an ensemble classification model for detection of the fake news that has achieved a better accuracy compared to the state-of-the-art.

186 citations

Posted Content
TL;DR: A comprehensive survey on blockchain for big data, focusing on up-to-date approaches, opportunities, and future directions is provided, including blockchain for secure big data acquisition, data storage, data analytics, and data privacy preservation.
Abstract: Big data has generated strong interest in various scientific and engineering domains over the last few years. Despite many advantages and applications, there are many challenges in big data to be tackled for better quality of service, e.g., big data analytics, big data management, and big data privacy and security. Blockchain with its decentralization and security nature has the great potential to improve big data services and applications. In this article, we provide a comprehensive survey on blockchain for big data, focusing on up-to-date approaches, opportunities, and future directions. First, we present a brief overview of blockchain and big data as well as the motivation behind their integration. Next, we survey various blockchain services for big data, including blockchain for secure big data acquisition, data storage, data analytics, and data privacy preservation. Then, we review the state-of-the-art studies on the use of blockchain for big data applications in different vertical domains such as smart city, smart healthcare, smart transportation, and smart grid. For a better understanding, some representative blockchain-big data projects are also presented and analyzed. Finally, challenges and future directions are discussed to further drive research in this promising area.

173 citations

Journal ArticleDOI
TL;DR: A crow search-based convolution neural networks model has been implemented in gesture recognition pertaining to the HCI domain and generates 100 percent training and testing accuracy that justifies the superiority of the model against traditional state-of-the-art models.
Abstract: Human–computer interaction (HCI) and related technologies focus on the implementation of interactive computational systems. The studies in HCI emphasize on system use, creation of new techniques that support user activities, access to information, and ensures seamless communication. The use of artificial intelligence and deep learning-based models has been extensive across various domains yielding state-of-the-art results. In the present study, a crow search-based convolution neural networks model has been implemented in gesture recognition pertaining to the HCI domain. The hand gesture dataset used in the study is a publicly available one, downloaded from Kaggle. In this work, a one-hot encoding technique is used to convert the categorical data values to binary form. This is followed by the implementation of a crow search algorithm (CSA) for selecting optimal hyper-parameters for training of dataset using the convolution neural networks. The irrelevant parameters are eliminated from consideration, which contributes towards enhancement of accuracy in classifying the hand gestures. The model generates 100 percent training and testing accuracy that justifies the superiority of the model against traditional state-of-the-art models.

114 citations


Cited by
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10 Mar 2020

2,024 citations

Journal ArticleDOI
TL;DR: This paper aims to provide a survey-based tutorial on potential applications and supporting technologies of Industry 5.0 from the perspective of different industry practitioners and researchers.

314 citations

Journal ArticleDOI
07 Apr 2021
TL;DR: In this paper, the authors provide a comprehensive survey of the current developments towards 6G and elaborate the requirements that are necessary to realize the 6G applications, and summarize lessons learned from state-of-the-art research and discuss technical challenges that would shed a new light on future research directions toward 6G.
Abstract: Emerging applications such as Internet of Everything, Holographic Telepresence, collaborative robots, and space and deep-sea tourism are already highlighting the limitations of existing fifth-generation (5G) mobile networks. These limitations are in terms of data-rate, latency, reliability, availability, processing, connection density and global coverage, spanning over ground, underwater and space. The sixth-generation (6G) of mobile networks are expected to burgeon in the coming decade to address these limitations. The development of 6G vision, applications, technologies and standards has already become a popular research theme in academia and the industry. In this paper, we provide a comprehensive survey of the current developments towards 6G. We highlight the societal and technological trends that initiate the drive towards 6G. Emerging applications to realize the demands raised by 6G driving trends are discussed subsequently. We also elaborate the requirements that are necessary to realize the 6G applications. Then we present the key enabling technologies in detail. We also outline current research projects and activities including standardization efforts towards the development of 6G. Finally, we summarize lessons learned from state-of-the-art research and discuss technical challenges that would shed a new light on future research directions towards 6G.

273 citations