Alwin Poulose

Dr. Alwin Poulose was born in Manjapra, Kerala, India, in 1992. He received a B.Sc. degree in computer maintenance and electronics from the Union Christian College, Aluva, Kerala, India, in 2012, the M.Sc. degree in electronics from the MES College Marampally, Kerala, India, in 2014, the M. Tech degree in communication systems from Christ University, Bangalore, India in 2017, and the Ph.D. degree in electronics and electrical engineering from Kyungpook National University, Daegu, South Korea in 2021. His research interests include indoor localization, human activity recognition, facial emotion recognition, and human behavior prediction. He is a reviewer of prominent engineering and science international journals and has served as a technical program committee member at several international conferences. He is currently a researcher at the Center for ICT & Automobile Convergence (CITAC), Kyungpook National University, Daegu, South Korea.

EDUCATION

2017/08/21 – 2021/08/31: Ph.D. Degree in Electronic and Electrical Engineering, Kyungpook National University, Daegu, South Korea.

2015/06/01 – 2017/05/21: M. Tech Degree in Electronics and Communication Engineering, Christ University, Bangalore, India.

2014/08/05 – 2015/04/25: Trainee for International English Language Testing System (IELTS), Newman's Academy, Angamaly, Kerala, India.

2012/07/02 – 2014/07/31: M.Sc. Degree in Electronics, MES College, Marampally, Kerala, India.

2009/07/01 – 2012/04/30: B. Sc. Degree in Computer Maintenance and Electronics, Aluva, Kerala, India.

RESEARCH INTERESTS

indoor localization, human activity recognition, facial emotion recognition, and human behavior prediction

Scopus Publications

Diversity-driven self-regulation for robust high-dimensional black-box optimization
Pritha Jana, Alwin Poulose
Expert Systems with Applications, 2026
Data augmentation for machine learning assisted pesticide detection from SERS
Thwahira Shirin Alampara, Abhishek Jayachandran, Shraddha Ramakrishna Bhat, Shyamala Thirunavukkuarasu, Alwin Poulose
Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy, 2026
Mothers to Newborns: A Two Decade Analysis of Female Nutrition and Neonatal Mortality Trends Across Indian States
Ananthika Sajith, Ananya J R, Ann Rose Saji, Megha P, Vaishnavi M, et al.
7th International Conference on Innovative Trends in Information Technology Icitiit 2026, 2026
Electroencephalogram-based emotion recognition: a comparative analysis of supervised machine learning algorithms
Anagha Prakash, Alwin Poulose
Data Science and Management, 2025
YOLO advances to its genesis: a decadal and comprehensive review of the You Only Look Once (YOLO) series
Ranjan Sapkota, Marco Flores-Calero, Rizwan Qureshi, Chetan Badgujar, Upesh Nepal, et al.
Artificial Intelligence Review, 2025
This review systematically examines the progression of the You Only Look Once (YOLO) object detection algorithms from YOLOv1 to the recently unveiled YOLOv12. Employing a reverse chronological analysis, this study examines the advancements introduced by YOLO algorithms, beginning with YOLOv12 and progressing through YOLO11 (or YOLOv11), YOLOv10, YOLOv9, YOLOv8, and subsequent versions to explore each version’s contributions to enhancing speed, detection accuracy, and computational efficiency in real-time object detection. Additionally, this study reviews the alternative versions derived from YOLO architectural advancements of YOLO-NAS, YOLO-X, YOLO-R, DAMO-YOLO, and Gold-YOLO. Moreover, the study highlights the transformative impact of YOLO models across five critical application areas: autonomous vehicles and traffic safety, healthcare and medical imaging, industrial manufacturing, surveillance and security, and agriculture. By detailing the incremental technological advancements in subsequent YOLO versions, this review chronicles the evolution of YOLO, and discusses the challenges and limitations in each of the earlier versions. The evolution signifies a path towards integrating YOLO with multimodal, context-aware, and Artificial General Intelligence (AGI) systems for the next YOLO decade, promising significant implications for future developments in AI-driven applications.
A Hybrid Deep Learning Model for Aromatic and Medicinal Plant Species Classification Using a Curated Leaf Image Dataset
Shareena E. M., D. Abraham Chandy, Shemi P. M., Alwin Poulose
Agriengineering, 2025
In the era of smart agriculture, accurate identification of plant species is critical for effective crop management, biodiversity monitoring, and the sustainable use of medicinal resources. However, existing deep learning approaches often underperform when applied to fine-grained plant classification tasks due to the lack of domain-specific, high-quality datasets and the limited representational capacity of traditional architectures. This study addresses these challenges by introducing a novel, well-curated leaf image dataset consisting of 39 classes of medicinal and aromatic plants collected from the Aromatic and Medicinal Plant Research Station in Odakkali, Kerala, India. To overcome performance bottlenecks observed with a baseline Convolutional Neural Network (CNN) that achieved only 44.94% accuracy, we progressively enhanced model performance through a series of architectural innovations. These included the use of a pre-trained VGG16 network, data augmentation techniques, and fine-tuning of deeper convolutional layers, followed by the integration of Squeeze-and-Excitation (SE) attention blocks. Ultimately, we propose a hybrid deep learning architecture that combines VGG16 with Batch Normalization, Gated Recurrent Units (GRUs), Transformer modules, and Dilated Convolutions. This final model achieved a peak validation accuracy of 95.24%, significantly outperforming several baseline models, such as custom CNN (44.94%), VGG-19 (59.49%), VGG-16 before augmentation (71.52%), Xception (85.44%), Inception v3 (87.97%), VGG-16 after data augumentation (89.24%), VGG-16 after fine-tuning (90.51%), MobileNetV2 (93.67), and VGG16 with SE block (94.94%). These results demonstrate superior capability in capturing both local textures and global morphological features. The proposed solution not only advances the state of the art in plant classification but also contributes a valuable dataset to the research community. Its real-world applicability spans field-based plant identification, biodiversity conservation, and precision agriculture, offering a scalable tool for automated plant recognition in complex ecological and agricultural environments.
Corrigendum to ‘Deep learning dives: Predicting anxiety in Zebrafish through novel tank assay analysis’ (Physiology & Behavior (2024) 287, 114696 (S0031938424002440), (10.1016/j.physbeh.2024.114696))
Anagha Muralidharan, Amrutha Swaminathan, Alwin Poulose
Physiology and Behavior, 2025
Anxiety in aquatics: Leveraging machine learning models to predict adult zebrafish behavior
Vartika Srivastava, Anagha Muralidharan, Amrutha Swaminathan, Alwin Poulose
Neuroscience, 2025
Optimizing Machine Learning Models for Human Activity Recognition via Feature Engineering and Selection
Vishak Viswalal, Alwin Poulose
6th International Conference on Control Communication and Computing Iccc 2025, 2025
Advancing Gastrointestinal Tract Cancer Treatment: A Comparative Study of State-of-the-Art Deep Learning Models for MRI Segmentation
Govindram Neware, Alwin Poulose
Etis International Conference on Emerging Technologies for Intelligent Systems Etis 2025, 2025
This paper investigates the performance of state-of-the-art deep learning models for segmenting the gastrointestinal (GI) tract in Magnetic Resonance Imaging (MRI) images, a critical step in radiotherapy planning for GI tract cancers. Manual segmentation of the GI tract is time-consuming, error-prone, and complicated by anatomical complexity and patient movement. To automate this process, we explore various deep learning techniques for their potential to provide accurate and efficient segmentation. Specifically, this study compares Feature Pyramid Networks (FPN), LinkNet, Pyramid Scene Parsing Networks (PSPNet), and traditional U-Net architectures and their variants. Using the publicly available UW Madison GI Tract Image Segmentation dataset, which includes 38,496 MRI scans with corresponding RLE-encoded masks, we evaluate architectures such as U-Net with different encoders (EfficientNetB1, MobileNetV2, and ResNet50), U-Net++ with EfficientNetB1, PSP-Net (EfficientNetB1 and ResNet34), FPN (EfficientNetB0 and EfficientNetB1) and LinkNet with EfficientNetB1. The models were trained using a standardized protocol over 30 epochs, with performance assessed through the Dice and Jaccard/IoU coefficients. Results indicate that the models achieved Dice scores ranging from 0.86 to 0.89, with no single model consistently out-performing the others. However, U-Net variations with residual connections demonstrated the most robust performance overall. This study provides valuable insights into the application of deep learning for medical image segmentation. It lays the groundwork for further research to enhance segmentation accuracy in GI cancer treatment, ultimately contributing to improved patient care and expedited treatment planning.
Harnessing Wi-Fi CSI for Enhanced Human Activity Recognition: A Feature-Driven Approach
Aparna B G, Alwin Poulose
Etis International Conference on Emerging Technologies for Intelligent Systems Etis 2025, 2025
From Wrist to Ankle: Understanding IMU Sensor Placement in Human Activity Recognition
Gouri Lakshmi S, Alwin Poulose
Etis International Conference on Emerging Technologies for Intelligent Systems Etis 2025, 2025
Empowering Autism Diagnosis Analysis with Power BI Visualizations
Jadov Menaka, Alwin Poulose
Etis International Conference on Emerging Technologies for Intelligent Systems Etis 2025, 2025
Deep Learning Architectures for 3D Shape Classification: A Study on PointNet and Voxel Grid-Based Models
Icoicc 2025 3rd International Conference on Intelligent and Cloud Computing, 2025
Refining Sorghum Weed Classification with Dimension Reduction Techniques in Machine Learning
Kondaveeti Tejaswi, Madala Vikas, Alwin Poulose
Etis International Conference on Emerging Technologies for Intelligent Systems Etis 2025, 2025
Enhancing Prediabetes Prediction Using Hybrid CNNs and SMOTE for Data Imbalance
Madala Vikas, Kondaveeti Tejaswi, Alwin Poulose
Etis International Conference on Emerging Technologies for Intelligent Systems Etis 2025, 2025
Analyzing the Effectiveness of Sobel and Laplacian Filters Integration in Facial Emotion Recognition
Abhiram D, Odelu Ojjela, Alwin Poulose
6th International Conference on Control Communication and Computing Iccc 2025, 2025
Tableau Driven Insights and Trends of Road Accidents in Kerala from 2018 to 2023
Kondaveeti Tejaswi, Madala Vikas, Alwin Poulose
6th International Conference on Control Communication and Computing Iccc 2025, 2025
Global Refugee Analysis: Insights into Asylum Applications, Demographics, and Resettlement Trends
Icoicc 2025 3rd International Conference on Intelligent and Cloud Computing, 2025
Advanced Brain Tumor Classification from MRI Images with Vision and Swin Transformer Models
Anjali Jain, Ankita Mishra, Gosala Bethany, Manjari Gupta, Alwin Poulose
Etis International Conference on Emerging Technologies for Intelligent Systems Etis 2025, 2025
Comprehensive Investigation of Machine Learning and Deep Learning Networks for Identifying Multispecies Tomato Insect Images
Chittathuru Himala Praharsha, Alwin Poulose, Chetan Badgujar
Sensors, 2024
Deep learning dives: Predicting anxiety in zebrafish through novel tank assay analysis
Anagha Muralidharan, Amrutha Swaminathan, Alwin Poulose
Physiology and Behavior, 2024
CBAM VGG16: An efficient driver distraction classification using CBAM embedded VGG16 architecture
Chittathuru Himala Praharsha, Alwin Poulose
Computers in Biology and Medicine, 2024
Agricultural object detection with You Only Look Once (YOLO) Algorithm: A bibliometric and systematic literature review
Chetan M Badgujar, Alwin Poulose, Hao Gan
Computers and Electronics in Agriculture, 2024
Melodic Precision: Unveiling the Impact of Recursive Feature Elimination on Music Genre Classification
Govindram Neware, Alwin Poulose
Icacc International Conference on Advances in Computing and Communications, 2024

RECENT SCHOLAR PUBLICATIONS

Diversity-driven self-regulation for robust high-dimensional black-box optimization
P Jana, A Poulose
Expert Systems with Applications 321, 132293 , 2026
2026
Citations: 1
Mothers to Newborns: A Two Decade Analysis of Female Nutrition and Neonatal Mortality Trends Across Indian States
A Sajith, JR Ananya, AR Saji, P Megha, M Vaishnavi, A Poulose
2026 International Conference on Innovative Trends in Information Technology … , 2026
2026
Learning to Color: An Empirical Study of Autoencoder Models for Deep Image Colorization
JR Ananya, M Vaishnavi
2025 International Conference on Robotics and Mechatronics (ICRM), 1-6 , 2025
2025
A Deep Learning-Based Image-to-Music Recommendation System Using Visual and Semantic Fusion
H Kumar, M Mridha, SG AK, A Poulose
2025 International Conference on Robotics and Mechatronics (ICRM), 1-6 , 2025
2025
Spike2Image: A Comparative Framework for Visual Reconstruction Using Biologically Inspired Neural Encoding
S Agarwal, A Poulose
2025 International Conference on Robotics and Mechatronics (ICRM), 1-6 , 2025
2025
Transformer-MIL and AdaBoost Fusion for Non-Invasive Depression Detection
AR Saji, P Megha, A Poulose
2025 International Conference on Robotics and Mechatronics (ICRM), 1-6 , 2025
2025
Data augmentation for machine learning assisted pesticide detection from SERS
TS Alampara, A Jayachandran, SR Bhat, S Thirunavukkuarasu, ...
Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 127090 , 2025
2025
Citations: 2
A Hybrid Deep Learning Model for Aromatic and Medicinal Plant Species Classification Using a Curated Leaf Image Dataset
S EM, DA Chandy, S PM, A Poulose
AgriEngineering 7 (8), 243 , 2025
2025
Citations: 7
YOLO advances to its genesis: A decadal and comprehensive review of the You Only Look Once (YOLO) series
R Sapkota, M Flores-Calero, R Qureshi, C Badgujar, U Nepal, A Poulose, ...
Artificial Intelligence Review 58 (9), 274 , 2025
2025
Citations: 388
Tableau Driven Insights and Trends of Road Accidents in Kerala from 2018 to 2023
K Tejaswi, M Vikas, A Poulose
2025 6th International Conference on Control, Communication and Computing … , 2025
2025
Optimizing Machine Learning Models for Human Activity Recognition via Feature Engineering and Selection
V Viswalal, A Poulose
2025 6th International Conference on Control, Communication and Computing … , 2025
2025
Citations: 2
Analyzing the Effectiveness of Sobel and Laplacian Filters Integration in Facial Emotion Recognition
D Abhiram, O Ojjela, A Poulose
2025 6th International Conference on Control, Communication and Computing … , 2025
2025
Global Refugee Analysis: Insights into Asylum Applications, Demographics, and Resettlement Trends
GH Bhagyasree, OS Yaswanth
2025 International Conference on Intelligent and Cloud Computing (ICoICC), 1-6 , 2025
2025
Deep Learning Architectures for 3D Shape Classification: A Study on PointNet and Voxel Grid-Based Models
OP Shamil, A Poulose
2025 International Conference on Intelligent and Cloud Computing (ICoICC), 1-7 , 2025
2025
Citations: 3
From wrist to ankle: Understanding IMU sensor placement in human activity recognition
A Poulose
2025 emerging technologies for intelligent systems (ETIS), 1-6 , 2025
2025
Citations: 11
Refining sorghum weed classification with dimension reduction techniques in machine learning
K Tejaswi, M Vikas, A Poulose
2025 Emerging Technologies for Intelligent Systems (ETIS), 1-6 , 2025
2025
Citations: 4
Enhancing prediabetes prediction using hybrid cnns and smote for data imbalance
M Vikas, K Tejaswi, A Poulose
2025 Emerging Technologies for Intelligent Systems (ETIS), 1-6 , 2025
2025
Citations: 1
Advancing gastrointestinal tract cancer treatment: a comparative study of state-of-the-art deep learning models for MRI segmentation
G Neware, A Poulose
2025 Emerging Technologies for Intelligent Systems (ETIS), 1-6 , 2025
2025
Citations: 3
Advanced brain tumor classification from mri images with vision and swin transformer models
A Jain, A Mishra, G Bethany, M Gupta, A Poulose
2025 Emerging Technologies for Intelligent Systems (ETIS), 1-5 , 2025
2025
Citations: 3
Empowering Autism Diagnosis Analysis with Power BI Visualizations
J Menaka, A Poulose
2025 Emerging Technologies for Intelligent Systems (ETIS), 1-6 , 2025
2025
Citations: 1

MOST CITED SCHOLAR PUBLICATIONS

Agricultural object detection with You Only Look Once (YOLO) Algorithm: A bibliometric and systematic literature review
CM Badgujar, A Poulose, H Gan
Computers and Electronics in Agriculture 223, 109090 , 2024
2024
Citations: 431
YOLO advances to its genesis: A decadal and comprehensive review of the You Only Look Once (YOLO) series
R Sapkota, M Flores-Calero, R Qureshi, C Badgujar, U Nepal, A Poulose, ...
Artificial Intelligence Review 58 (9), 274 , 2025
2025
Citations: 388
UWB indoor localization using deep learning LSTM networks
A Poulose, DS Han
Applied Sciences 10 (18), 6290 , 2020
2020
Citations: 258
An indoor position-estimation algorithm using smartphone IMU sensor data
A Poulose, OS Eyobu, DS Han
Ieee Access 7, 11165-11177 , 2019
2019
Citations: 248
iSPLInception: an inception-ResNet deep learning architecture for human activity recognition
M Ronald, A Poulose, DS Han
IEEE Access 9, 68985-69001 , 2021
2021
Citations: 240
Hybrid indoor localization using IMU sensors and smartphone camera
A Poulose, DS Han
Sensors 19 (23), 5084 , 2019
2019
Citations: 141
A sensor fusion framework for indoor localization using smartphone sensors and Wi-Fi RSSI measurements
A Poulose, J Kim, DS Han
Applied Sciences 9 (20), 4379 , 2019
2019
Citations: 124
The extensive usage of the facial image threshing machine for facial emotion recognition performance
JH Kim, A Poulose, DS Han
Sensors 21 (6), 2026 , 2021
2021
Citations: 96
Localization error analysis of indoor positioning system based on UWB measurements
A Poulose, OS Eyobu, M Kim, DS Han
2019 Eleventh International Conference on Ubiquitous and Future Networks … , 2019
2019
Citations: 85
Hybrid deep learning model based indoor positioning using Wi-Fi RSSI heat maps for autonomous applications
A Poulose, DS Han
Electronics 10 (1), 2 , 2020
2020
Citations: 79
Performance analysis of sensor fusion techniques for heading estimation using smartphone sensors
A Poulose, B Senouci, DS Han
IEEE Sensors Journal 19 (24), 12369-12380 , 2019
2019
Citations: 70
An accurate indoor user position estimator for multiple anchor UWB localization
A Poulose, Ž Emeršič, OS Eyobu, DS Han
2020 international conference on information and communication technology … , 2020
2020
Citations: 69
Attention-based multi-learning approach for speech emotion recognition with dilated convolution
S Kakuba, A Poulose, DS Han
IEEE Access 10, 122302-122313 , 2022
2022
Citations: 64
Deep learning-based speech emotion recognition using multi-level fusion of concurrent features
S Kakuba, A Poulose, DS Han
IEEE Access 10, 125538-125551 , 2022
2022
Citations: 60
HIT HAR: Human Image Threshing Machine for Human Activity Recognition Using Deep Learning Models
A Poulose, JH Kim, DS Han
Computational Intelligence and Neuroscience 2022 (Article ID 1808990), 21 , 2022
2022
Citations: 59
Performance analysis of fingerprint matching algorithms for indoor localization
A Poulose, DS Han
2020 international conference on artificial intelligence in information and … , 2020
2020
Citations: 57
Feature-based deep LSTM network for indoor localization using UWB measurements
A Poulose, DS Han
2021 International Conference on Artificial Intelligence in Information and … , 2021
2021
Citations: 56
Deep learning approaches for bimodal speech emotion recognition: Advancements, challenges, and a multi-learning model
S Kakuba, A Poulose, DS Han
IEEE Access 11, 113769-113789 , 2023
2023
Citations: 55
CBAM VGG16: An efficient driver distraction classification using CBAM embedded VGG16 architecture
CH Praharsha, A Poulose
Computers in biology and medicine 180, 108945 , 2024
2024
Citations: 54
Foreground extraction based facial emotion recognition using deep learning xception model
A Poulose, CS Reddy, JH Kim, DS Han
2021 Twelfth International Conference on Ubiquitous and Future Networks … , 2021
2021
Citations: 45