|
INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
Imp Links for Author
Imp Links for Reviewer
Research Area
Subscribe IJSDR
Visitor Counter
Copyright Infringement Claims
Indexing Partner
|
Published Paper Details
|
|
| Paper Title: | Deep Learning to Identify Plant Species |
| Authors Name: | Fayas Rasheed , Liz George |
| Unique Id: | IJSDR2303249 |
| Published In: | Volume 8 Issue 3, March-2023 |
| Abstract: | Abstract: Deep learning is the method that has the ability to develop precise models for recognizing images. Deep learning has shown potential for automating the process of identifying various plant species from images of their leaves, flowers, and fruits. To reduce noise and improve the plant features, the input images undergo pre-processing. The deep learning model is then trained using a sizable labelled dataset of plant images. Once trained, the model can accurately recognize the plant species from new images. While automated plant classification systems typically rely on leaf shape as the main feature for identification, leaves also have other characteristics that can contribute to more precise classification, such as their texture, vein patterns, and color. This technology has the potential to be applied in various fields, such as agriculture, botany, and environmental conservation, to help identify and monitor different plant species in their natural surroundings. However, as with any deep learning application, the quality of the training data and the neural network architecture design are essential factors that can have a significant impact on the system's performance. |
| Keywords: | Index Terms: Deep learning, Species, Architecture (key words) |
| Cite Article: | "Deep Learning to Identify Plant Species", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 3, page no.1444 - 1447, March-2023, Available :http://www.ijsdr.org/papers/IJSDR2303249.pdf |
| Downloads: | 000337354 |
| Publication Details: | Published Paper ID: IJSDR2303249 Registration ID:204977 Published In: Volume 8 Issue 3, March-2023 DOI (Digital Object Identifier): Page No: 1444 - 1447 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijsdr.org
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | DOAJ : Directory of Open Access Journals |
| DRJI | Index Copernicus International | Scribd | DocStoc |
Track Paper
Important Links
Conference Proposal
ISSN
 |
 |
DOI (A digital object identifier)
  Providing A digital object identifier by DOI How to GET DOI and Hard Copy Related |
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
 |
 |
 |
Social Media
Indexing Partner |
|||
| Copyright © 2024 - All Rights Reserved - IJSDR | |||
Facebook Twitter Instagram LinkedIn