A5022573866- Smart Agriculture and AI
- Digital Imaging for Blood Diseases
- AI in Service Interactions
- Bioinformatics and Genomic Networks
- Social Robot Interaction and HRI
- Gene expression and cancer classification
- AI in cancer detection
- Anomaly Detection Techniques and Applications
- Plant Disease Management Techniques
- IoT-based Smart Home Systems
- Mosquito-borne diseases and control
- Malaria Research and Control
University of Copenhagen
2024
Radboud University Nijmegen
2021
Savitribai Phule Pune University
2019
Agriculture plays a significant role in meeting food needs and providing security for the increasingly growing global population, which has increased by 0.88% since 2022. Plant diseases can reduce production affect security. Worldwide crop loss due to plant disease is estimated be around 14.1%. The lack of proper identification at early stages infection result inappropriate control measures. Therefore, automatic diagnosis are highly recommended. Lack availability large amounts data that not...
The most common cancer among women is breast cancer. Around 12% of are affected by it all over the world. Recurrent a term used for which returns even after successful treatment. This research aims to use Machine learning detect and predict recurrence cancer; compare models using different metrics like accuracy, precision, etc. built can help effectively. All Wisconsin Prognostic Breast Cancer Dataset(WPBC). Multiple Linear Regression, Support Vector Machine, was build RBF Kernel...
This work demonstrates an experimental implementation of a helper bot using IBM Watson. It is primarily aimed at people who know English as second language. With the help Watson Assistant tool, chatbot uses APIs like Google Translate API, Text to Speech SimpleWIki and Musixmatch provide features rich responses, translation regional languages, text speech conversion facilities, useful information in simpler English, displaying music lyrics for languages. particularly helpful those are newly...
Mosquito ecology and behavior malaria parasite development display marked sensitivity to weather, in particular temperature precipitation. Therefore, climate change is expected profoundly affect epidemiology its transmission, spatiotemporal distribution consequent disease burden. However, transmission also complicated by other factors (e.g. urbanization, socioeconomic development, genetics, drug resistance) which together constitute a highly complex, dynamical system, where the influence of...