Výsledky vyhledávání - "Ramesh Vatambeti"

Akademický článek

Enhanced stock market forecasting using dandelion optimization-driven 3D-CNN-GRU classification

Autor: B. N. Jagadesh, N. V. RajaSekhar Reddy, Pamula Udayaraju, Vijay Kumar Damera, Ramesh Vatambeti, M. S. Jagadeesh, Ch. Koteswararao

Publikováno v: Scientific Reports, Vol 14, Iss 1, Pp 1-20 (2024)

Abstract The global interest in market prediction has driven the adoption of advanced technologies beyond traditional statistical models. This paper explores the use of machine learning and deep learning techniques for stock market forecasting. We pr

Externí odkaz: https://doaj.org/article/030edb98c56a4ef1a44fa330bed65574

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Akademický článek

Enhanced botnet detection in IoT networks using zebra optimization and dual-channel GAN classification

Autor: SK Khaja Shareef, R. Krishna Chaitanya, Srinivasulu Chennupalli, Devi Chokkakula, K. V. D. Kiran, Udayaraju Pamula, Ramesh Vatambeti

Publikováno v: Scientific Reports, Vol 14, Iss 1, Pp 1-19 (2024)

Abstract The Internet of Things (IoT) permeates various sectors, including healthcare, smart cities, and agriculture, alongside critical infrastructure management. However, its susceptibility to malware due to limited processing power and security pr

Externí odkaz: https://doaj.org/article/99cae7d4c0bd47a1b064fb5d9799fce6

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Akademický článek

Enhanced deep learning models for automatic fish species identification in underwater imagery

Autor: Siri D, Gopikrishna Vellaturi, Shaik Hussain Shaik Ibrahim, Srikanth Molugu, Venkata Subbaiah Desanamukula, Raviteja Kocherla, Ramesh Vatambeti

Publikováno v: Heliyon, Vol 10, Iss 15, Pp e35217- (2024)

Underwater cameras are crucial in marine ecology, but their data management needs automatic species identification. This study proposes a two-stage deep learning approach. First, the Unsharp Mask Filter (UMF) preprocesses images. Then, an enhanced re

Externí odkaz: https://doaj.org/article/4991842b52bb47de95124a3d126cb3fa

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Akademický článek

Analyzing Public Sentiment on the Amazon Website: A GSK-Based Double Path Transformer Network Approach for Sentiment Analysis

Autor: Lella Kranthi Kumar, Venkata Nagaraju Thatha, Pamula Udayaraju, D. Siri, G. Uday Kiran, B. N. Jagadesh, Ramesh Vatambeti

Publikováno v: IEEE Access, Vol 12, Pp 28972-28987 (2024)

Sentiment Analysis (SA) holds considerable significance in comprehending public perspectives and conducting precise opinion-based evaluations, making it a prominent theme in natural language processing research. With the increasing trend of online sh

Externí odkaz: https://doaj.org/article/be12f1b1f96b4e1e8714b712f4f8e885

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Akademický článek

Prediction of DDoS attacks in agriculture 4.0 with the help of prairie dog optimization algorithm with IDSNet

Autor: Ramesh Vatambeti, D. Venkatesh, Gowtham Mamidisetti, Vijay Kumar Damera, M. Manohar, N. Sudhakar Yadav

Publikováno v: Scientific Reports, Vol 13, Iss 1, Pp 1-13 (2023)

Abstract Integrating cutting-edge technology with conventional farming practices has been dubbed “smart agriculture” or “the agricultural internet of things.” Agriculture 4.0, made possible by the merging of Industry 4.0 and Intelligent Agric

Externí odkaz: https://doaj.org/article/1a1f45810b664bc3aafee448cb736750

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Akademický článek

Hybrid deep learning model with enhanced sunflower optimization for flood and earthquake detection

Autor: Phalguna Krishna E S, Venkata Nagaraju Thatha, Gowtham Mamidisetti, Srihari Varma Mantena, Phanikanth Chintamaneni, Ramesh Vatambeti

Publikováno v: Heliyon, Vol 9, Iss 10, Pp e21172- (2023)

Natural catastrophes may strike anywhere at any moment and cause widespread destruction. Most people do not have the necessary catastrophe preparedness knowledge or awareness. The combination of a flood and an earthquake can cause widespread destruct

Externí odkaz: https://doaj.org/article/7d6f643eb9f7489487d3fcb37ae12ea2

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Akademický článek

Segmentation Using the IC2T Model and Classification of Diabetic Retinopathy Using the Rock Hyrax Swarm-Based Coordination Attention Mechanism

Autor: B. N. Jagadesh, M. Ganesh Karthik, D. Siri, S. K. Khaja Shareef, Srihari Varma Mantena, Ramesh Vatambeti

Publikováno v: IEEE Access, Vol 11, Pp 124441-124458 (2023)

Diabetic Retinopathy (DR) evaluations are increasingly being automated using artificial intelligence. Diabetes-related retinal vascular disease is a major cause of blindness and visual impairment worldwide. Therefore, automated DR detection devices w

Externí odkaz: https://doaj.org/article/855d0a8645974e20bd43343c3e48833d

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