Plant disease diagnosis using deep transfer learning architectures- VGG19, MobileNetV2 and Inception-V3
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.
المؤلفون الرئيسيون: | Kobra, Khadija-Tul, Suham, Rahmatul Rashid, Fairooz, Maisha |
---|---|
مؤلفون آخرون: | Uddin, Jia |
التنسيق: | أطروحة |
اللغة: | English |
منشور في: |
Brac University
2022
|
الموضوعات: | |
الوصول للمادة أونلاين: | http://hdl.handle.net/10361/17334 |
مواد مشابهة
-
Myocardial infarction detection using ECG signal applying deep learning techniques - ConvNet, VGG16, InceptionV3 and MobileNet
بواسطة: Promita, Samanta Tabassum, وآخرون
منشور في: (2022) -
Comparative analysis between Inception-v3 and other learning systems using facial expressions detection
بواسطة: Nivrito, AKM, وآخرون
منشور في: (2016) -
Deep neural network models for COVID-19 diagnosis from CT-Scan, explainability and analysis using trained models
بواسطة: Islam, Tahsin, وآخرون
منشور في: (2021) -
A comparative study of lung cancer prediction using deep learning
بواسطة: Mugdho, Aka Mohammad, وآخرون
منشور في: (2023) -
Detection of prodromal parkinson’s disease with fMRI data and deep neural network approaches
بواسطة: Shahriar, Farhan, وآخرون
منشور في: (2021)