Thippa Reddy Gadekallu
Biographic Data
| ID | 8158732 |
|---|---|
| NAME | Thippa Reddy Gadekallu |
| GIVEN NAMES | Thippa Reddy |
| FAMILY NAME | Gadekallu |
| SIGNATURE | GADEKALLU T R |
| AFFILIATIONS | Zhejiang A & F University |
| ORCID | 0000-0003-0097-801X |
| VERIFIED | Yes |
| TOTAL WORKS | 10 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 10 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Fortifying Deepfake Detection With AI and Postquantum Cryptography-Based Watermarking Technique
In the digital era, deepfakes have become a critical threat to social media platforms and online information systems, undermining public trust and enabling misinformation campaigns at unprecedented scales. The advancements of artificial intelligence have promoted the rapid development of deepfake technology which enables the manipulation of visual content in highly realistic ways. While this technology holds potential for creative applications, i…
IoST-Enabled Segmentation of Obscenity for Media Security Using Multifilter Federated W-Net
The emergence of social media in the COVID-19 has contributed to the proliferation of explicit materials, which are frequently used by cybercriminals. To overcome this, the federated fusion W-Net (Gabor + PL) model, an intelligence of social things (IoST) enabled cooperative learning model is proposed that can be used to solve the problem of segmentation and moderation of obscene images. It is a hybrid of Gabor filtering to extract texture and po…
Feature Jointly-Based Knowledge Enhancement Model for Multimodal Sentiment Analysis
Political Response Analysis of Twitter/X Users Using Topic-Based Sentiment Analysis
The heavy use of social media platforms is generating a high volume of affective data over the internet. This data is being used by researchers in various domains for prediction, qualitative, and quantitative analytical problems such as stock market prediction, opinion mining of online reviews on products, events, and many more. This article leverages X data for the political response analysis of users towards the 2019 Indian General election. In…
Deep Learning Model for Interpretability and Explainability of Aspect-Level Sentiment Analysis Based on Social Media
The interactive attention graph convolution network (IAGCN), a novel model proposed in this article, will revolutionize aspect-level sentiment analysis (SA). IAGCN effectively addresses these key features, in contrast to prior research that ignored the meaning of aspect terms and their relationship with context. The model combines a modified dynamic weighting layer with bidirectional long short-term memory (BiLSTM) to accurately acquire context. …
Trust-Aware Social-System-Inspired Clustering for Large-Scale Knowledge Discovery in Wireless Sensor Networks
Wireless sensor networks (WSNs) can be conceptualized as large-scale, dynamic social systems where nodes interact to achieve collective objectives. These networks generate extensive data through interactions, offering opportunities for large-scale knowledge discovery to optimize operations and enhance resilience. However, challenges such as limited resources and susceptibility to distributed denial-of-service (DDoS) attacks necessitate efficient …
InfusedHeart
In the undertaken study, we have used a customized dataset termed ``Cardiac-200'' and the benchmark dataset ``PhysioNet.'' which contains 1500 heartbeat acoustic event samples (without augmentation) and 1950 samples (with augmentation) heartbeat acoustic events such as normal, murmur, extrasystole, artifact, and other unlabeled heartbeat acoustic events. The primary reason for designing a customized dataset, ``cardiac-200,'' is to balance the tot…
Blockchain-Based Two-Stage Federated Learning With Non-IID Data in IoMT System
The Internet of Medical Things (IoMT) has a bright future with the development of smart mobile devices. Information technology is also leading changes in the healthcare industry. IoMT devices can detect patient signs and provide treatment guidance and even instant diagnoses through technologies, such as artificial intelligence (AI) and wireless communication. However, conventional centralized machine learning approaches are often difficult to app…
Federated learning enabled digital twins for smart cities
Deep learning and medical image processing for coronavirus (Covid-19) pandemic
No prominent works on this page.
Deep learning and medical image processing for coronavirus (Covid-19) pandemic
Federated learning enabled digital twins for smart cities
Blockchain-Based Two-Stage Federated Learning With Non-IID Data in IoMT System
The Internet of Medical Things (IoMT) has a bright future with the development of smart mobile devices. Information technology is also leading changes in the healthcare industry. IoMT devices can detect patient signs and provide treatment guidance and even instant diagnoses through technologies, such as artificial intelligence (AI) and wireless communication. However, conventional centralized machine learning approaches are often difficult to app…
InfusedHeart
In the undertaken study, we have used a customized dataset termed ``Cardiac-200'' and the benchmark dataset ``PhysioNet.'' which contains 1500 heartbeat acoustic event samples (without augmentation) and 1950 samples (with augmentation) heartbeat acoustic events such as normal, murmur, extrasystole, artifact, and other unlabeled heartbeat acoustic events. The primary reason for designing a customized dataset, ``cardiac-200,'' is to balance the tot…
Deep Learning Model for Interpretability and Explainability of Aspect-Level Sentiment Analysis Based on Social Media
The interactive attention graph convolution network (IAGCN), a novel model proposed in this article, will revolutionize aspect-level sentiment analysis (SA). IAGCN effectively addresses these key features, in contrast to prior research that ignored the meaning of aspect terms and their relationship with context. The model combines a modified dynamic weighting layer with bidirectional long short-term memory (BiLSTM) to accurately acquire context. …
Trust-Aware Social-System-Inspired Clustering for Large-Scale Knowledge Discovery in Wireless Sensor Networks
Wireless sensor networks (WSNs) can be conceptualized as large-scale, dynamic social systems where nodes interact to achieve collective objectives. These networks generate extensive data through interactions, offering opportunities for large-scale knowledge discovery to optimize operations and enhance resilience. However, challenges such as limited resources and susceptibility to distributed denial-of-service (DDoS) attacks necessitate efficient …
Fortifying Deepfake Detection With AI and Postquantum Cryptography-Based Watermarking Technique
In the digital era, deepfakes have become a critical threat to social media platforms and online information systems, undermining public trust and enabling misinformation campaigns at unprecedented scales. The advancements of artificial intelligence have promoted the rapid development of deepfake technology which enables the manipulation of visual content in highly realistic ways. While this technology holds potential for creative applications, i…
IoST-Enabled Segmentation of Obscenity for Media Security Using Multifilter Federated W-Net
The emergence of social media in the COVID-19 has contributed to the proliferation of explicit materials, which are frequently used by cybercriminals. To overcome this, the federated fusion W-Net (Gabor + PL) model, an intelligence of social things (IoST) enabled cooperative learning model is proposed that can be used to solve the problem of segmentation and moderation of obscene images. It is a hybrid of Gabor filtering to extract texture and po…
Feature Jointly-Based Knowledge Enhancement Model for Multimodal Sentiment Analysis
Political Response Analysis of Twitter/X Users Using Topic-Based Sentiment Analysis
The heavy use of social media platforms is generating a high volume of affective data over the internet. This data is being used by researchers in various domains for prediction, qualitative, and quantitative analytical problems such as stock market prediction, opinion mining of online reviews on products, events, and many more. This article leverages X data for the political response analysis of users towards the 2019 Indian General election. In…
Computer Science (7 works) · Artificial Intelligence (5 works) · Computer security (3 works) · Data science (3 works) · Deep learning (3 works) · Machine learning (3 works) · Sentiment analysis (3 works) · Sentiment Analysis and Opinion Mining (3 works) · Social media (3 works) · Advanced Data and IoT Technologies (2 works)