CFNN for Identifying Poisonous Plants
Identification of poisonous plants is a hard challenge for researchers because of the great similarity between poisonous and non- poisonous plants. Traditional methods to identify poisonous plant can be tiresome, therefore, automated poisonous plants identification system is needed. In this wor...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
University of Baghdad, College of Science for Women
2023-06-01
|
| Series: | مجلة بغداد للعلوم |
| Subjects: | |
| Online Access: | https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/7874 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849247572413120512 |
|---|---|
| author | Israa Mohammed Hassoon Shaymaa Akram Hantoosh |
| author_facet | Israa Mohammed Hassoon Shaymaa Akram Hantoosh |
| author_sort | Israa Mohammed Hassoon |
| collection | DOAJ |
| description |
Identification of poisonous plants is a hard challenge for researchers because of the great similarity between poisonous and non- poisonous plants. Traditional methods to identify poisonous plant can be tiresome, therefore, automated poisonous plants identification system is needed. In this work, cascade forward neural network framework is proposed to identify poisonous plants based on their leaves. The proposed system was evaluated on both (poisonous leaves/non-poisonous leaves) which are collected using smart phone and internet. Combination of shape features and statistical features are extracted from leaf then fed to cascade-forward neural network which used TRAINLM function for training. 500 samples of leaf images are used, 250 samples are poisonous, the remaining 250 samples are non-poisonous.300 samples used in training, 200 samples for testing. Our system is achieved an accuracy value of 99.5%.
|
| format | Article |
| id | doaj-art-308441c4538b40b2afbd7c646e81fde2 |
| institution | Kabale University |
| issn | 2078-8665 2411-7986 |
| language | English |
| publishDate | 2023-06-01 |
| publisher | University of Baghdad, College of Science for Women |
| record_format | Article |
| series | مجلة بغداد للعلوم |
| spelling | doaj-art-308441c4538b40b2afbd7c646e81fde22025-08-20T03:58:11ZengUniversity of Baghdad, College of Science for Womenمجلة بغداد للعلوم2078-86652411-79862023-06-01203(Suppl.)10.21123/bsj.2023.7874CFNN for Identifying Poisonous PlantsIsraa Mohammed Hassoon 0Shaymaa Akram Hantoosh 1Department of Mathematics, Collage of Science, University of Mustansiriyah (UOM), Baghdad, IraqMiddle Technical University, Continuous Education Center, Baghdad,Iraq Identification of poisonous plants is a hard challenge for researchers because of the great similarity between poisonous and non- poisonous plants. Traditional methods to identify poisonous plant can be tiresome, therefore, automated poisonous plants identification system is needed. In this work, cascade forward neural network framework is proposed to identify poisonous plants based on their leaves. The proposed system was evaluated on both (poisonous leaves/non-poisonous leaves) which are collected using smart phone and internet. Combination of shape features and statistical features are extracted from leaf then fed to cascade-forward neural network which used TRAINLM function for training. 500 samples of leaf images are used, 250 samples are poisonous, the remaining 250 samples are non-poisonous.300 samples used in training, 200 samples for testing. Our system is achieved an accuracy value of 99.5%. https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/7874Cascade Forward Neural Network (CFNN), First Order Statistical Features, Poisonous Plants, Shape Features, TRAINLM Function |
| spellingShingle | Israa Mohammed Hassoon Shaymaa Akram Hantoosh CFNN for Identifying Poisonous Plants مجلة بغداد للعلوم Cascade Forward Neural Network (CFNN), First Order Statistical Features, Poisonous Plants, Shape Features, TRAINLM Function |
| title | CFNN for Identifying Poisonous Plants |
| title_full | CFNN for Identifying Poisonous Plants |
| title_fullStr | CFNN for Identifying Poisonous Plants |
| title_full_unstemmed | CFNN for Identifying Poisonous Plants |
| title_short | CFNN for Identifying Poisonous Plants |
| title_sort | cfnn for identifying poisonous plants |
| topic | Cascade Forward Neural Network (CFNN), First Order Statistical Features, Poisonous Plants, Shape Features, TRAINLM Function |
| url | https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/7874 |
| work_keys_str_mv | AT israamohammedhassoon cfnnforidentifyingpoisonousplants AT shaymaaakramhantoosh cfnnforidentifyingpoisonousplants |