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Jac Fredo Agastinose Ronickom
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- affiliation: Nanyang Technological University, Singapore
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2020 – today
- 2025
- [j13]Vinay Kumar Barigala, Swarubini PJ, Sriram Kumar P, Nagarajan Ganapathy, Karthik P. A., Deepesh Kumar
, Jac Fredo Agastinose Ronickom
Evaluating the effectiveness of machine learning in identifying the optimal facial electromyography location for emotion detection. Biomed. Signal Process. Control. 100: 107012 (2025) - 2024
- [j12]Abirami Selvaraj, Tikaram
Automated Multi-Class Seizure-Type Classification System Using EEG Signals and Machine Learning Algorithms. IEEE Access 12: 136524-136541 (2024) - [j11]Praveen Kumar Govarthan
Emotion classification using electrocardiogram and machine learning: A study on the effect of windowing techniques. Expert Syst. Appl. 254: 124371 (2024) - [j10]Sriram Kumar P
Optimal Electrodermal Activity Segment for Enhanced Emotion Recognition Using Spectrogram-Based Feature Extraction and Machine Learning. Int. J. Neural Syst. 34(5): 2450027:1-2450027:22 (2024) - [j9]Chetan Rakshe
Autism spectrum disorder diagnosis using fractal and non-fractal-based functional connectivity analysis and machine learning methods. Neural Comput. Appl. 36(20): 12565-12585 (2024) - [j8]Chetan Rakshe, Suja Kunneth, Soumya Sundaram, Murugappan Murugappan
Correction: Autism spectrum disorder diagnosis using fractal and non-fractal-based functional connectivity analysis and machine learning methods. Neural Comput. Appl. 36(20): 12587 (2024) - [j7]Sriram Kumar P
Deep Learning-Based Automated Emotion Recognition Using Multimodal Physiological Signals and Time-Frequency Methods. IEEE Trans. Instrum. Meas. 73: 1-12 (2024) - 2023
- [c13]Vaibhavi Gupta, Gokul Manoj, Aditi Bhattacharya, Sandeep Singh Sengar
A Framework to Diagnose Autism Spectrum Disorder Using Morphological Connectivity of sMRI and XGBoost. EFMI-STC 2023: 33-37 - [c12]Vaibhav Jain, Sandeep Singh Sengar, Jac Fredo Agastinose Ronickom:
Age-Specific Diagnostic Classification of ASD Using Deep Learning Approaches. EFMI-STC 2023: 267-271 - [c11]Praveen Kumar Govarthan
Deep Learning Framework for Categorical Emotional States Assessment Using Electrodermal Activity Signals. ICIMTH 2023: 40-43 - [c10]Lokesh Naidu Lebaka
Automated Emotion Recognition System Using Blood Volume Pulse and XGBoost Learning. ICIMTH 2023: 52-55 - [c9]Chetan Rakshe
Diagnostic Classification of ASD Using Fractal Functional Connectivity of fMRI and Logistic Regression. ICIMTH 2023: 60-63 - [c8]Ravi Ratnaik
Diagnostic Classification of ASD Improves with Structural Connectivity of DTI and Logistic Regression. ICIMTH 2023: 64-67 - [c7]Abirami Selvaraj, Swarubini PJ
Multi-Class Seizure Type Classification Using Features Extracted from the EEG. ICIMTH 2023: 68-71 - [c6]Praveen Kumar Sriram Kumar Pa Govarthan
Identifying the Optimal Location of Facial EMG for Emotion Detection Using Logistic Regression. ICIMTH 2023: 81-84 - [c5]Sriram Kumar P
Comparative Analysis of Electrodermal Activity Decomposition Methods in Emotion Detection Using Machine Learning. MIE 2023: 73-77 - [c4]Abdul Aleem Shaik Gadda
Optimization of Pre-Ictal Interval Time Period for Epileptic Seizure Prediction Using Temporal and Frequency Features. MIE 2023: 232-236 - [c3]Jahanvi Jeswani
Low Valence Low Arousal Stimuli: An Effective Candidate for EEG-Based Biometrics Authentication System. MIE 2023: 257-261 - [c2]Praveen Kumar Pragyaa Govarthan
Differential Gene Expression Data Analysis of ASD Using Random Forest. MIE 2023: 1047-1051 - [i1]Gokul Manoj, Sandeep Singh Sengar, Jac Fredo Agastinose Ronickom:
Age-Stratified Differences in Morphological Connectivity Patterns in ASD: An sMRI and Machine Learning Approach. CoRR abs/2308.07356 (2023) - 2022
- [j6]Sreelakshmi Shaji, Jac Fredo Agastinose Ronickom, Anandh Kilpattu Ramaniharan, Ramakrishnan Swaminathan:
Study on the effect of extreme learning machine and its variants in differentiating Alzheimer conditions from selective regions of brain MR images. Expert Syst. Appl. 209: 118250 (2022) - [j5]Rakshit Mittal
Time-Sliced Architecture for Efficient Accelerator to Detrend High-Definition Electroencephalograms. IEEE Trans. Instrum. Meas. 71: 1-9 (2022) - [c1]Vaibhav Jain
Automated Diagnosis of Autism Spectrum Disorder Condition Using Shape Based Features Extracted from Brainstem. MIE 2022: 53-57 - 2021
- [j4]Rakshit Mittal
Modified-MaMeMi filter bank for efficient extraction of brainwaves from electroencephalograms. Biomed. Signal Process. Control. 69: 102927 (2021) - [j3]Maya A. Reiter, Afrooz Jahedi
Performance of machine learning classification models of autism using resting-state fMRI is contingent on sample heterogeneity. Neural Comput. Appl. 33(8): 3299-3310 (2021) - [j2]Rakshit Mittal
Low-Power Hardware Accelerator for Detrending Measured Biopotential Data. IEEE Trans. Instrum. Meas. 70: 1-9 (2021)
2010 – 2019
- 2014
- [j1]Agastinose Ronickom Jac Fredo
Segmentation and analysis of brain subcortical regions using regularized multiphase level set in autistic MR images. Int. J. Imaging Syst. Technol. 24(3): 256-262 (2014)
Coauthor Index
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