Deep Learning based Medicinal Plants Leaf Recognition

This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2022.

Մատենագիտական մանրամասներ
Հիմնական հեղինակ:	Mahalanabish, Tonusri
Այլ հեղինակներ:	Rabiul Alam, Md. Golam
Ձևաչափ:	Թեզիս
Լեզու:	English
Հրապարակվել է:	Brac University 2023
Խորագրեր:	Deep Neural Network CNN VGG19 Machine Learning SVM HOG Feature GrayScale Feature Grad-CAM Cognitive learning theory (Deep learning)
Առցանց հասանելիություն:	http://hdl.handle.net/10361/18032

id	10361-18032
record_format	dspace
spelling	10361-180322023-03-28T21:01:51Z Deep Learning based Medicinal Plants Leaf Recognition Mahalanabish, Tonusri Rabiul Alam, Md. Golam Department of Computer Science and Engineering, Brac University Deep Neural Network CNN VGG19 Machine Learning SVM HOG Feature GrayScale Feature Grad-CAM Cognitive learning theory (Deep learning) This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 60-64). Plants assume a significant part in Earth’s nature by giving food, cover and keeping a solid environment.These plants contain some significant therapeutic qualities. Due to having fewer negative side effects and being more affordable than contemporary medicine, medicinal plants are receiving interest in the pharmaceutical business.In this work, I tried to classify the plant’s images through classical methods and Deep neural network.30 medicinal plants leaves are represented by 1835 images in the proposed dataset.First, I applied CNN to classify the images and got 65.66% ac curacy.Then I applied SVM with Normal features, GrayScale features, HOG fea tures and combined features extraction and got 72.28% accuracy for Normal fea tures,73.91% accuracy for GrayScale features, 79.34% accuracy for HOG features and 80.0% for Combined feature extraction.Next I applied the VGG-19 pre-trained model and got 96.74% accuracy.At last, I applied a GradCam explainable AI method to interpret the results generated from VGG19.From all these experiments, I got the best accuracy for the VGG19 pretrained model.That’s why I used Grad Cam on the VGG19 results for getting the explanation for the predictions. Tonusri Mahalanabish M. Computer Science and Engineering 2023-03-28T08:00:56Z 2023-03-28T08:00:56Z 2022 2022-09 Thesis ID: 22173011 http://hdl.handle.net/10361/18032 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 64 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Deep Neural Network CNN VGG19 Machine Learning SVM HOG Feature GrayScale Feature Grad-CAM Cognitive learning theory (Deep learning)
spellingShingle	Deep Neural Network CNN VGG19 Machine Learning SVM HOG Feature GrayScale Feature Grad-CAM Cognitive learning theory (Deep learning) Mahalanabish, Tonusri Deep Learning based Medicinal Plants Leaf Recognition
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2022.
author2	Rabiul Alam, Md. Golam
author_facet	Rabiul Alam, Md. Golam Mahalanabish, Tonusri
format	Thesis
author	Mahalanabish, Tonusri
author_sort	Mahalanabish, Tonusri
title	Deep Learning based Medicinal Plants Leaf Recognition
title_short	Deep Learning based Medicinal Plants Leaf Recognition
title_full	Deep Learning based Medicinal Plants Leaf Recognition
title_fullStr	Deep Learning based Medicinal Plants Leaf Recognition
title_full_unstemmed	Deep Learning based Medicinal Plants Leaf Recognition
title_sort	deep learning based medicinal plants leaf recognition
publisher	Brac University
publishDate	2023
url	http://hdl.handle.net/10361/18032
work_keys_str_mv	AT mahalanabishtonusri deeplearningbasedmedicinalplantsleafrecognition
_version_	1814307001691275264

Deep Learning based Medicinal Plants Leaf Recognition

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