Message from the Organizing Secretary 4th IEEE North Karnataka Subsection Flagship International Conference Holistic Engineering for Sustainable Development Nkcon 2025, 2025
ML based Fish Species Image Classification Medha Kudari, Anupama S Nandeppanavar, Puneeth N Thotad 2025 5th International Conference on Intelligent Technologies Conit 2025, 2025 Fish species classification is a critical task in marine biology and fisheries management, providing essential data for ecological studies and conservation efforts. This paper explores the application of deep learning techniques to classify fish species using image data. We employed four pre-trained convolutional neural network (CNN) models—VGG19, InceptionV3 and MobileNetV2 to categorize images into ten distinct fish species: Black Sea Sprat, Gilt-Head Bream, Horse Mackerel, Red Mullet, Red Sea Bream, Sea Bass, Shrimp, Striped Red Mullet, Trout, and Fighting. The dataset, sourced from Kaggle, comprises 7,000 color images, equally distributed across the ten species, and was split into $70 \%$ for training and $30 \%$ for validation. Each image, ranging in size from 100 KB to 200 KB and in PNG format, was used to train and validate the models. Our results indicate that the chosen deep learning models can achieve high accuracy in classifying fish species, with InceptionV3 and MobileNetV2 showing particularly strong performance. This study demonstrates the potential of deep learning in automating fish species identification, which can significantly aid in biodiversity monitoring and resource management.
Deep Learning for Automatic Detection of Musical Instruments in Audio Signals Anjali N Patil, Medha Kudari, Anupama S Nandeppanavar, Puneeth N Thotad 2025 5th Asian Conference on Innovation in Technology Asiancon 2025, 2025 One essential element of music understanding is the ability to recognize the instruments in an auditory recording. The rapidly evolving field of Automatic Musical Instrument Detection (AMID) provides for the identification of instruments in audio signals without the use for the human intervention, hence meeting this need. In this project, it presents a deep learning-based approach to musical instrument classification that is both accurate and effective. We use a curated dataset with 15 instrument classes and 500 audio samples per class to train and assess five cutting-edge models, including VGG16, DenseNet201, ResNet50V2, MobileNetV2, and XceptionNet, using Convolutional Neural Networks (CNNs). Before being entered into the models, the audio recordings undergo preprocessing to create spectrogram pictures, which collect both temporal and spatial information. Multiple dataset splits were used in the experiments to confirm each architecture's resilience. Every model demonstrated its efficacy by achieving classification accuracies above 90%. We also created an end-to-end system that predicts the appropriate instrument class from an input raw audio file.
An NLP System for Automated Indian Penal Code Assignment from Crime Reports Anupama S Nandeppanavar, Sachin.S. Hebbalakar, Medha Kudari, Puneeth N Thotad, Shanta Kallur 4th IEEE North Karnataka Subsection Flagship International Conference Holistic Engineering for Sustainable Development Nkcon 2025, 2025
Image-Based Identification and Classification of Dry Fruits Using Deep Learning Sania Allabhax Agadi, Medha Kudari, Anupama S Nandeppanavar, Puneeth N Thotad, Shanta Kallur 2025 5th Asian Conference on Innovation in Technology Asiancon 2025, 2025 With the increasing importance of dried fruit classification in the food industry for sorting, packaging, and quality assurance purposes, we utilized artificial intelligence to create an automated classifier of dried fruits, which are almonds, cashew nuts, raisins and figs, with three varieties of each type (12 classes in total). A custom dataset containing still images was created and image augmentations (e.g., flipping, rotating, etc.) were applied to increase variety. We ensured the same number of images per class so as to maintain fairness. Five deep learning architectures were trained and evaluated using VGG16, DenseNet121, InceptionV3, Swin Transformer, and ShuffleNetV2, across different train/test splits (50:50, 60:40, 70:30, and 80:20). We achieved models that exceeded desired accuracy for classification tasks, which indicates that deep learning was indeed effective in achieving dried fruit classification. Based on the results, the utilization of AI-based automation for dried fruit sorting can significantly increase the speed and consistency of sorting and processing dried fruits in the food industry.
AudioBrief: An Audio Transcription and Summarization System Using Whisper and Transformer-Based NLP Models M Kudari, D Kadam, AS Nandeppanavar, PN Thotad, S Kallur 2025 IEEE North Karnataka Subsection Flagship International Conference … , 2025 2025
An NLP System for Automated Indian Penal Code Assignment from Crime Reports AS Nandeppanavar, SS Hebbalakar, M Kudari, PN Thotad, S Kallur 2025 IEEE North Karnataka Subsection Flagship International Conference … , 2025 2025
ChildSafe: An Offline Android-Based Screen Time Management and App Restriction System for Children S Kallur, JV Ganti, M Kudari, AS Nandeppanavar, PN Thotad 2025 IEEE North Karnataka Subsection Flagship International Conference … , 2025 2025
Smart Farming with AI: Comparative Analysis of Deep Learning Models for Cauliflower Disease Identification PN Thotad, M Kalakeri, M Kudari, AS Nandeppanavar 2025 IEEE North Karnataka Subsection Flagship International Conference … , 2025 2025
Intelligent Crop Surveillence: A Machine Learning-Based Approach for Precision Agriculture P Thotad, SS Kallur, A Hamza, M Kudari, AS Nandeppanavar 2025 Global Conference on Information Technology and Communication Networks … , 2025 2025
Multi-Stage ML-Based Prediction and Classification of Liver Cirrhosis Progression P Thotad, V Patil, M Kudari, S Kallur, S Yaligar, A Nandeppanavar 2025 5th Asian Conference on Innovation in Technology (ASIANCON), 1-6 , 2025 2025
A Data Driven Machine Learning Model for Autism Spectrum Disorder Detection S Bagalkot, V Patil, S Yaligar, P Thotad, S Kallur 2025 5th Asian Conference on Innovation in Technology (ASIANCON), 1-5 , 2025 2025
Deep Learning for Automatic Detection of Musical Instruments in Audio Signals AN Patil, M Kudari, AS Nandeppanavar, PN Thotad 2025 5th Asian Conference on Innovation in Technology (ASIANCON), 1-6 , 2025 2025
Image-Based Identification and Classification of Dry Fruits Using Deep Learning SA Agadi, M Kudari, AS Nandeppanavar, PN Thotad, S Kallur 2025 5th Asian Conference on Innovation in Technology (ASIANCON), 1-6 , 2025 2025
ML based Fish Species Image Classification M Kudari, AS Nandeppanavar, PN Thotad 2025 5th International Conference on Intelligent Technologies (CONIT), 1-6 , 2025 2025
Smart Surveillance: Real-Time Crowd Detection and Density Estimation with CNNs V Hiremani, P Thotad, S Yaligar, SS Kallur, V Patil, R Sapna International Conference on Smart Computing and Informatics, 33-44 , 2025 2025
Cricket shot classification using Deep Learning S Kallur, PN Thotad, S Yaligar 2024 Global Conference on Communications and Information Technologies (GCCIT … , 2024 2024 Citations: 2
Boosting-based machine learning approaches for diabetes prediction using Indian demographic and health survey data S Kallur, S Yaligar, PN Thotad 2024 IEEE North Karnataka subsection flagship international conference … , 2024 2024 Citations: 3
A Machine Learning based approach for Bird Migration Detection and feature analysis with SHAP M Kudari, AS Nandeppanavar, P Thotad, S Jatti, S Koti 2024 IEEE North Karnataka Subsection Flagship International Conference … , 2024 2024 Citations: 4
Identification and Segmentation of Polyp Using Deep Learning Approaches S Yaligar, SS Kallur, V Patil, PN Thotad 2024 4th Asian Conference on Innovation in Technology (ASIANCON), 1-6 , 2024 2024
An Efficient Model for Early Detection of Maize Leaf Disease using Deep Learning Approaches S Kallur, S Yaligar, PN Thotad 2024 4th Asian Conference on Innovation in Technology (ASIANCON), 1-6 , 2024 2024 Citations: 2
Analysis of type-2 diabetes datasets using sampling techniques PT Geeta Bharamagoudar, Basavaraj Anami International Journal of Medical Engineering and Informatics , 2024 2024
Bharatanatyam hasta mudra categorization using deep learning approaches AS Nandeppanavar, SS Kallur, P Thotad, VA Sankannavar 2023 IEEE North Karnataka Subsection Flagship International Conference … , 2023 2023 Citations: 5
An efficient model for plant disease detection in agriculture using deep learning approaches PN Thotad, S Kallur, A Nandeppanavar 2023 4th IEEE global conference for advancement in technology (GCAT), 1-6 , 2023 2023 Citations: 18
Mental Health Tracker Using Machine Learning Approaches PN Thotad, S Kallur, L Mundaragi, SH Kadam 2023 4th IEEE Global Conference for Advancement in Technology (GCAT), 1-5 , 2023 2023 Citations: 12
MOST CITED SCHOLAR PUBLICATIONS
Diabetic foot ulcer detection using deep learning approaches PN Thotad, GR Bharamagoudar, BS Anami Sensors International 4, 100210 , 2023 2023 Citations: 126
Diabetes disease detection and classification on Indian demographic and health survey data using machine learning methods PN Thotad, GR Bharamagoudar, BS Anami Diabetes & Metabolic Syndrome: Clinical Research & Reviews 17 (1), 102690 , 2023 2023 Citations: 56
Automatic question generator using natural language processing P Thotad, S Kallur, S Amminabhavi Journal of Pharmaceutical Negative Results 13 (10), 1231-1236 , 2022 2022 Citations: 23
An efficient model for plant disease detection in agriculture using deep learning approaches PN Thotad, S Kallur, A Nandeppanavar 2023 4th IEEE global conference for advancement in technology (GCAT), 1-6 , 2023 2023 Citations: 18
Mental Health Tracker Using Machine Learning Approaches PN Thotad, S Kallur, L Mundaragi, SH Kadam 2023 4th IEEE Global Conference for Advancement in Technology (GCAT), 1-5 , 2023 2023 Citations: 12
Predictive analysis of diabetes mellitus using decision tree approach P Thotad, GR Bharamagoudar, BS Anami 2022 2nd Asian Conference on Innovation in Technology (ASIANCON), 1-7 , 2022 2022 Citations: 12
Boosting-based machine learning approaches for diabetes prediction using Indian demographic and health survey-2021 data PN Thotad, GR Bharamagoudar, SS Kallur 2023 Citations: 7
SURVEY ON MINING DIABETES DATA AND ITS APPLICATIONS ON DIAGNOSING METHODS IN DISEASE MANAGEMENT USING BIG DATA. P Thotad, GR Bharamagoudar, SG Totad, S Kallur International Journal of Advanced Research in Computer Science 9 (1) , 2018 2018 Citations: 6
Bharatanatyam hasta mudra categorization using deep learning approaches AS Nandeppanavar, SS Kallur, P Thotad, VA Sankannavar 2023 IEEE North Karnataka Subsection Flagship International Conference … , 2023 2023 Citations: 5
A Machine Learning based approach for Bird Migration Detection and feature analysis with SHAP M Kudari, AS Nandeppanavar, P Thotad, S Jatti, S Koti 2024 IEEE North Karnataka Subsection Flagship International Conference … , 2024 2024 Citations: 4
Boosting-based machine learning approaches for diabetes prediction using Indian demographic and health survey data S Kallur, S Yaligar, PN Thotad 2024 IEEE North Karnataka subsection flagship international conference … , 2024 2024 Citations: 3
A Machine Learning-based Diagnosis and Prediction of Diabetes Mellitus Disease PN Thotad 2023 Citations: 3
Cricket shot classification using Deep Learning S Kallur, PN Thotad, S Yaligar 2024 Global Conference on Communications and Information Technologies (GCCIT … , 2024 2024 Citations: 2
An Efficient Model for Early Detection of Maize Leaf Disease using Deep Learning Approaches S Kallur, S Yaligar, PN Thotad 2024 4th Asian Conference on Innovation in Technology (ASIANCON), 1-6 , 2024 2024 Citations: 2
AudioBrief: An Audio Transcription and Summarization System Using Whisper and Transformer-Based NLP Models M Kudari, D Kadam, AS Nandeppanavar, PN Thotad, S Kallur 2025 IEEE North Karnataka Subsection Flagship International Conference … , 2025 2025
An NLP System for Automated Indian Penal Code Assignment from Crime Reports AS Nandeppanavar, SS Hebbalakar, M Kudari, PN Thotad, S Kallur 2025 IEEE North Karnataka Subsection Flagship International Conference … , 2025 2025
ChildSafe: An Offline Android-Based Screen Time Management and App Restriction System for Children S Kallur, JV Ganti, M Kudari, AS Nandeppanavar, PN Thotad 2025 IEEE North Karnataka Subsection Flagship International Conference … , 2025 2025
Smart Farming with AI: Comparative Analysis of Deep Learning Models for Cauliflower Disease Identification PN Thotad, M Kalakeri, M Kudari, AS Nandeppanavar 2025 IEEE North Karnataka Subsection Flagship International Conference … , 2025 2025
Intelligent Crop Surveillence: A Machine Learning-Based Approach for Precision Agriculture P Thotad, SS Kallur, A Hamza, M Kudari, AS Nandeppanavar 2025 Global Conference on Information Technology and Communication Networks … , 2025 2025
Multi-Stage ML-Based Prediction and Classification of Liver Cirrhosis Progression P Thotad, V Patil, M Kudari, S Kallur, S Yaligar, A Nandeppanavar 2025 5th Asian Conference on Innovation in Technology (ASIANCON), 1-6 , 2025 2025
