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SAHEBGOUD HANAMANTRAY KARADDI
Kishkinda University, Ballari, MIT Academy of Engineering, Poojya Doddappa Appa College of Engineering, RL Jalappa Institute of Technology, VIT-AP Campus
About
I sahebgoud Hanamantraya Karaddi persuing Ph.D. in VIT-ap campus from July 2021 in SENSE department. Research interests are Image Processing, signal processing, Deep learning and machine learning
Employment
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Kishkinda University, Ballari Associate Professor2025 - Present
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MIT Academy of Engineering Assistant Professor2024 - 2025
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VIT-AP Campus research scholar2021 - 2024
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Malla Reddy College of Engineering & Technology Assistant Professor2020 - 2021
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Malla Reddy Engineering College Assistant Professor2017 - 2020
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Malla Reddy Engineering College Assistant Professor2016 - 2017
Education
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Poojya Doddappa Appa College of Engineering M.TECH2012 - 2015
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RL Jalappa Institute of Technology B.E.2008 - 2012
Projects & Funding
Projects & funding information is unavailable.
Publications (20)
- Deep Fusion of VGG19 and ConvMixer With Superlet Transform for Cognitive Load Detection Save
- Segmentation and Classification of Pulmonary Diseases Using Artificial Neural Networks and Otsu-Region-Based Method from Chest Radiographs Save
- Sleep Stage Classification Using Variational Mode Decomposition and Wrapper-Based Feature Selection From the Single Channel EEG Save
- Coronary artery disease detection using deep integration of vision transformer and extended LSTM from cardiac multi-modal images Save
- Softflatten-Net: A Deep Convolutional Neural Network Design for Monkeypox Classification From Digital Skin Lesions Images Save
- Automated Metal Surface Flaws Detection Using Convolutional Neural Network and Deep Visualization Analysis Save
- Automated multi-class classification of lung diseases from CXR-images using pre-trained convolutional neural networks Save
- Detection of COVID-19 using CoviNet and VGG-16 Models Save
- Study of SQ-Net behavior using t-SNE activation by Classification of Lung Diseases in Chest Radiographs. Save
- Deep learning model for prediction of cancer with stage level varying parameter and analysis of gene expression Save