Paper Title
Metallic Petals: TPU-based Flower Classification
Article Identifiers
Authors
Tadikonda Harshitha , Lakshmi Likhitha Komarina , Jahnavi Geda , Bhuvana Mogali
Keywords
Abstract
Automated flower classification plays a pivotal role in various domains, from ecological studies to agriculture and beyond .The work uses a cutting-edge deep learning model for picture categorization and makes use of a sizable dataset with a variety of flower species. The study leverages a comprehensive dataset of diverse floral species, employing a state-of-the-art deep learning model for image classification. The integration of TPUs into the classification pipeline is explored, unlocking unprecedented computational speeds, and enabling the scalability of the model. Results indicate a significant boost in classification accuracy, showcasing the potential of TPUs in accelerating flower classification tasks. This research not only contributes to the field of automated image classification but also underscores the utility of TPUs in expediting complex machine learning computations.
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How To Cite (APA)
Tadikonda Harshitha, Lakshmi Likhitha Komarina, Jahnavi Geda, & Bhuvana Mogali (July-2024). Metallic Petals: TPU-based Flower Classification. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(7), a56-a62. https://ijnrd.org/papers/IJNRD2407007.pdf
Issue
Volume 9 Issue 7, July-2024
Pages : a56-a62
Other Publication Details
Paper Reg. ID: IJNRD_224276
Published Paper Id: IJNRD2407007
Downloads: 000121989
Research Area: Engineering
Country: Vijayawada, AndhraPradesh, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2407007.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2407007
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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
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