Springer Conference Presentation at ANTIC 2024 on Medicinal Plant Leaf Identification
The Department of Computer Science, Gauhati University and Hinton Research Lab, is pleased to announce the presentation of a research paper at the 4th International Conference on Advanced Network Technologies and Intelligent Computing (ANTIC-2024) held at Banaras Hindu University (BHU), Varanasi, India.
Deepjyoti Chetia presented the research paper titled “Identification of Traditional Medicinal Plant Leaves Using an Effective Deep Learning Model and Self-Curated Dataset” at the conference. The research addresses the growing need for intelligent and automated medicinal plant identification systems using modern Artificial Intelligence and Computer Vision techniques.
The work focuses on the development of a robust deep learning-based framework capable of recognizing medicinal plant species from leaf images collected through a carefully curated dataset. The proposed approach aims to support biodiversity conservation, herbal medicine documentation, and technology-driven healthcare applications.
The presentation highlighted several key aspects of the research, including:
- Development of a self-curated medicinal plant dataset
- Deep learning-based image classification techniques
- Feature extraction and plant species recognition
- Challenges in real-world medicinal plant identification
- Applications in biodiversity conservation and digital herbal repositories
The study demonstrates how Artificial Intelligence can assist researchers, students, healthcare practitioners, and conservationists in accurately identifying medicinal plants through image-based analysis.
The paper was accepted and published in the Springer Communications in Computer and Information Science (CCIS) conference proceedings, providing international visibility to the research work and contributing to the growing field of AI-assisted biodiversity informatics.
The conference brought together researchers, academicians, and industry experts from across the globe to discuss recent advancements in intelligent computing, artificial intelligence, machine learning, and network technologies.
The Department congratulates Deepjyoti Chetia on this achievement and appreciates his contribution toward advancing research in Computer Vision, Deep Learning, and Medicinal Plant Informatics.
