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Dr Sriram Kumar P

vidwan id: 347589
Male

Assistant Professor (Senior Grade),

Expertise

  • Telecommunications

Publications

Total Articles 8
Books 0
Proceedings 0

Publications

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Scopus

Citations 5
h-index 1

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Citations 0
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Bio

Signal systems, VLSI, Basic Electronics, Machine learning, and Deep learning

Personal Details

  • Male
  • Assistant Professor (Senior Grade)
  • Modallaguda (V), Nandigama(M)
Ph.D
Other Institute 2024
MASTER OF ENGINEERING
Vasavi College of Engineering 2009
B.Tech
Other Institute 2007
Assistant Professor (Senior Grade) Dec 2024 – Present
Unknown Organization
Associate Professor Jul 2024 – Nov 2024
Malla Reddy University | Information Technology
Assistant Professor Feb 2012 – Jun 2024
Goka Raju Ranga Raju Institute of Engineering & Technology | Electronics and Communication Engineering
Assistant Professor Jun 2010 – Apr 2011
Jyothishmathi Institute of Technology and Science | ECE

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A R

Dr A R Jac Fredo

Indian Institute of Technology (BHU), Varanasi

Scholarly Work

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Scholarly Publications

Emotion Classification Through Optimal Segments of EDA and Texture Analysis of Time-Encoded Images With Artificial Intelligence

Open Access
article

Deep Learning-Based Automated Emotion Recognition Using Multi modal Physiological Signals and Time-Frequency Methods

Open Access
article

Optimal Electrodermal Activity Segment for Enhanced Emotion Recognition Using Spectrogram-Based Feature Extraction and Machine Learning

Open Access
Article

Emotion classification using electrocardiogram and machine learning: A study on the effect of windowing techniques

Open Access
article
Authors: Praveen Kumar Govarthan, Sriram Kumar P

A COMPARATIVE ANALYSIS OF EDA DECOMPOSITION METHODS FOR IMPROVED EMOTION RECOGNITION

Open Access
article

ECG based Categorical emotion classification using time-domain features and Machine Learning

Open Access
article

ELECTRODERMAL ACTIVITY-BASED ANALYSIS OF EMOTION RECOGNITION USING TEMPORALMORPHOLOGICAL FEATURES AND MACHINE LEARNING ALGORITHMS

Open Access
article

Evaluating the effectiveness of machine learning in identifying the optimal facial electromyography location for emotion detection

Open Access
article
Authors: Barigala Vinay Kumar a, Swarubini P.J. b, Sriram Kumar P