Classifying insect pests from image data using deep learning
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.
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| Dil: | English |
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Brac University
2022
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| Online Erişim: | http://hdl.handle.net/10361/16914 |
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10361-169142022-06-06T21:01:31Z Classifying insect pests from image data using deep learning Mohsin, Md. Raiyan Bin Ramisa, Sadia Afrin Saad, Mohammad Rabbani, Shahreen Husne Tamkin, Salwa Ashraf, Faisal Bin Reza, Md. Tanzim Department of Computer Science and Engineering, Brac University IP102 Insect pest Transfer learning Data augmentation Classification Cognitive learning theory (Deep learning) Machine learning. Artificial intelligence This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 48-50). The fact that insecticidal pests impair significant agricultural productivity has become one of the main challenges in agriculture. There are, nevertheless, several requirements for a high-performing automated system that can detect pest insects from vast amounts of visual data. We employed deep learning approaches to correctly identify insect species from large volumes of data in this study model and explainable AI to decide which part of the photos is used to categorize the insects from the data. We chose to deal with the large-scale IP102 dataset since we worked with a large dataset. There are almost 75,000 pictures in this collection, divided into 102 categories. We ran state-of-the-art tests on the unique IP102 data set to evaluate our proposed solution. We used five different Deep Neural Networks (DNN) models for image classification: VGG19, ResNet50, EfficientNetB5, DenseNet121, InceptionV3, and implemented the LIME-based XAI (Explainable Artificial Intelligence) framework. DenseNet121 performed best across all classes, and it was also employed to detect crop-specific insect species. The classification accuracy for eight specific crops ranged from 46.31% to 95.36%. Moreover, we have compared our prediction performance to that of earlier articles to assess the efficacy of our research. Md. Raiyan Bin Mohsin Sadia Afrin Ramisa Mohammad Saad Shahreen Husne Rabbani Salwa Tamkin B. Computer Science 2022-06-06T07:09:40Z 2022-06-06T07:09:40Z 2022 2022-01 Thesis ID 18101639 ID 18101469 ID 14101135 ID 18101134 ID 18101511 http://hdl.handle.net/10361/16914 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. 50 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
IP102 Insect pest Transfer learning Data augmentation Classification Cognitive learning theory (Deep learning) Machine learning. Artificial intelligence |
| spellingShingle |
IP102 Insect pest Transfer learning Data augmentation Classification Cognitive learning theory (Deep learning) Machine learning. Artificial intelligence Mohsin, Md. Raiyan Bin Ramisa, Sadia Afrin Saad, Mohammad Rabbani, Shahreen Husne Tamkin, Salwa Classifying insect pests from image data using deep learning |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. |
| author2 |
Ashraf, Faisal Bin |
| author_facet |
Ashraf, Faisal Bin Mohsin, Md. Raiyan Bin Ramisa, Sadia Afrin Saad, Mohammad Rabbani, Shahreen Husne Tamkin, Salwa |
| format |
Thesis |
| author |
Mohsin, Md. Raiyan Bin Ramisa, Sadia Afrin Saad, Mohammad Rabbani, Shahreen Husne Tamkin, Salwa |
| author_sort |
Mohsin, Md. Raiyan Bin |
| title |
Classifying insect pests from image data using deep learning |
| title_short |
Classifying insect pests from image data using deep learning |
| title_full |
Classifying insect pests from image data using deep learning |
| title_fullStr |
Classifying insect pests from image data using deep learning |
| title_full_unstemmed |
Classifying insect pests from image data using deep learning |
| title_sort |
classifying insect pests from image data using deep learning |
| publisher |
Brac University |
| publishDate |
2022 |
| url |
http://hdl.handle.net/10361/16914 |
| work_keys_str_mv |
AT mohsinmdraiyanbin classifyinginsectpestsfromimagedatausingdeeplearning AT ramisasadiaafrin classifyinginsectpestsfromimagedatausingdeeplearning AT saadmohammad classifyinginsectpestsfromimagedatausingdeeplearning AT rabbanishahreenhusne classifyinginsectpestsfromimagedatausingdeeplearning AT tamkinsalwa classifyinginsectpestsfromimagedatausingdeeplearning |
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