Dr.Vijay Kumar Gugulothu
Government Polytechnic ,Masab Tank,Hyderabad, Technical Education
About
Dr. Vijay Kumar Gugulothu is currently working as Head of Computer Engineering at Government Polytechnic, Masab Tank, Hyderabad in the Department of Technical Education, Telangana, India. He received the M.Tech Degree in Computer Science & Engineering (2009) from University College of Engineering, Osmania University, Hyderabad, India, the Bachelor of Engineering (B.E) Degree (1997) from Osmania University, Hyderabad. Ph.D in Computer Science & Engineering from KL University, Hyderabad. His current research interest includes Machine Learning, Artificial Learning and Deep Learning.
He has 25+ years of Teaching Experience. He also has 8 years of research experience. He has published research papers in reputed national and international journals
Employment
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Government Polytechnic ,Masab Tank,Hyderabad Head of Computer Science Engineering
Education
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Technical Education B.Tech1993 - 1997
Projects & Funding
Projects & funding information is unavailable.
Publications (9)
- An Interpretable Multi-Modal Ensemble Framework for Breast Cancer Analysis Using Imaging, Omics and Biomedical Literature Save
- Red nucleus region segmentation-based brain tumor classification and stage estimation using GLRN-SGNet and Deep-2C-MHONN Save
- A novel deep learning approach for the detection and classification of lung nodules from CT images Save
- A novel EZS-MSCA and SeLu SqueezeNet-based lung tumor detection and classification Save
- An early prediction and classification of lung nodule diagnosis on CT images based on hybrid deep learning techniques Save
- An automatic classification of pulmonary nodules for lung cancer diagnosis using novel LLXcepNN classifier Save
- A Proficient GK-KMA Based Segmentation and Lung Nodule Detection in CT Images Using PTRNN Save
- An Early Prediction and Classification of Lung Nodule Diagnosis on CT Images Based on Hybrid Deep Learning Techniques Save
- Classification of IRS LISS-III IMAGES by using artificial neural networks Save