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@article{196814,
        author = {Manasi Namdev Musale and Shraddha Tanaji Sarate and Priyanka Dinkar Patil and Akshata Jaysing Patil},
        title = {Flower Recognition System Using Deep Learning and Image Captioning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {4273-4277},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=196814},
        abstract = {Conventional flower identification techniques demand human labor and specialized knowledge. In order to automatically identify flower species, this study suggests a Flower Recognition System that uses deep learning techniques. Flower recognition is crucial for environmental monitoring, botany, and agriculture. pictures. The system generates meaningful descriptions of the observed flowers using BLIP for image caption creation and YOLOv8 for object identification. Streamlit is used to create an intuitive web interface that lets users upload or take pictures for prediction. For research and record-keeping purposes, the system further keeps prediction history in a MySQL database. According to experimental results, the suggested system can reliably identify flowers and produce pertinent captions with a high degree of confidence.},
        keywords = {Flower Recognition, Deep Learning, YOLOv8, Image Captioning, Streamlit},
        month = {April},
        }