Plant disease diagnosis using deep transfer learning architectures- VGG19, MobileNetV2 and Inception-V3

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.

Библиографические подробности
Главные авторы:	Kobra, Khadija-Tul, Suham, Rahmatul Rashid, Fairooz, Maisha
Другие авторы:	Uddin, Jia
Формат:	Диссертация
Язык:	English
Опубликовано:	Brac University 2022
Предметы:	Plant diseases VGG19 MobileNetV2 Inception-v3 Crop Cognitive learning theory (Deep learning) Plant diseases > Diagnosis
Online-ссылка:	http://hdl.handle.net/10361/17334

Схожие документы

Myocardial infarction detection using ECG signal applying deep learning techniques - ConvNet, VGG16, InceptionV3 and MobileNet
по: Promita, Samanta Tabassum, и др.
Опубликовано: (2022)

Comparative analysis between Inception-v3 and other learning systems using facial expressions detection
по: Nivrito, AKM, и др.
Опубликовано: (2016)

Deep neural network models for COVID-19 diagnosis from CT-Scan, explainability and analysis using trained models
по: Islam, Tahsin, и др.
Опубликовано: (2021)

A comparative study of lung cancer prediction using deep learning
по: Mugdho, Aka Mohammad, и др.
Опубликовано: (2023)

Detection of prodromal parkinson’s disease with fMRI data and deep neural network approaches
по: Shahriar, Farhan, и др.
Опубликовано: (2021)

Skin disease detection and classification using deep learning
по: Shuvon, Mehedi Hasan, и др.
Опубликовано: (2022)

Analyzing students’ concentration in online courses through Webcam
по: Asif, Md., и др.
Опубликовано: (2024)

An efficient deep learning approach to detect retinal disease using optical coherence tomographic images
по: Khan, Farhan Sakib, и др.
Опубликовано: (2022)

Multi-classification Network for Detecting Skin Diseases using Deep Learning and XAI
по: Athina, Fahima Hasan, и др.
Опубликовано: (2022)

A hybrid FL-Enabled ensemble approach for lung disease diagnosis leveraging fusion of SWIN transformer and CNN
по: Chowdhury, Asif Hasan, и др.
Опубликовано: (2023)

Detection of skin diseases using deep learning
по: Shodoy, Masuk Ur Rahman
Опубликовано: (2024)

An efficient deep learning approach for detecting Alzheimer’s disease using brain images
по: Sani, Mehedi Hasan, и др.
Опубликовано: (2022)

Automatic waste classification using deep learning and computer vision techniques
по: Akash, MD., и др.
Опубликовано: (2023)

Kidney Disease detection and classification from CT Images using Watershed Segmentation and Deep Learning.
по: Hossain, Mohammad Sakib, и др.
Опубликовано: (2023)

Citrus leaf disease detection by image processing
по: Chowdhury, Mahir Faisal, и др.
Опубликовано: (2024)

A hybrid FL-enabled ensemble approach for lung disease diagnosis leveraging fusion of SWIN transformer and CNN
по: Chowdhury, Asif Hasan, и др.
Опубликовано: (2023)

Identifying brain abnormalities using image processing and CNN models
по: Talukder, Ismat Shehrin, и др.
Опубликовано: (2021)

Skin cancer classification for seven types of skin lesions
по: Rahman, Md. Tawsifur, и др.
Опубликовано: (2024)

Smoke detection using deep Convolutional neural network
по: Niloy, Wahidul Hasan, и др.
Опубликовано: (2021)

Explainable breast cancer detection from Histopathology images using transfer learning and XAI
по: Farabi, Farhan, и др.
Опубликовано: (2023)

Alzheimer’s Disease detection and classification using transfer learning techniques and ensembling operations on convolutional neural networks
по: Awwal, Alvina, и др.
Опубликовано: (2021)

Detection of intracranial hemorrhage on CT scan images using convolutional neural network
по: Rahman, Afridi Ibn, и др.
Опубликовано: (2022)

Tomato leaf disease detection using convolutional neural network
по: Hasan, Md. Riazul, и др.
Опубликовано: (2023)

An efficient deep learning approach to predict heart failure from image data using ejection fraction
по: Tanvir, Nazmul Karim, и др.
Опубликовано: (2023)

A deep learning approach for pneumonia classiﬁcation from chest X-Ray images with ensemble modelling and explainable AI
по: Akhter, Nasrin
Опубликовано: (2023)

In-silico based vaccine development: targeting nucleocapsid protein of SARS-CoV-2.
по: Iva, Yesmine Akter
Опубликовано: (2022)

An efficient deep learning approach to detect citrus leaves disease
по: Emon, Shaharear Hossain, и др.
Опубликовано: (2024)

Critical retinal disease detection from optical coherence tomography images by deep convolutional neural network and explainable machine learning
по: Datta, Pranab, и др.
Опубликовано: (2021)

Covid-19 infected lung detection using machine learning
по: Islam, Md. Muntaha, и др.
Опубликовано: (2022)

Plant leaf disease identification
по: Hasan Mahin, Mohammad Rakibul, и др.
Опубликовано: (2024)

Real-time crime detection using convolutional LSTM and YOLOv7
по: Sakiba, Cyrus, и др.
Опубликовано: (2023)

A deep learning approach to depression detection based on Convolutional Neural Networks and Transfer Learning
по: Sarmi, Kaniz Fatima, и др.
Опубликовано: (2022)

Simulation based distracted driver detection system using alcohol sensor and fusion of bioelectric signals to disseminate them through V2V/V2I to alleviate risky driving
по: Sikder, Md. Sarfaraj, и др.
Опубликовано: (2019)

Domestication, production and utilization of new crops /
Опубликовано: (1997)

A text book of plant pathology /
по: Ashrafuzzaman, Hasan
Опубликовано: (1991)

An interpretable diagnosis of retinal diseases using vision transformer and Grad-CAM
по: Bhuiyan, Mahdi Hasan, и др.
Опубликовано: (2024)

Smart detection and classification of fungal disease in rice plants using image processing techniques
по: Rashed, Akib, и др.
Опубликовано: (2024)

V.S. Naipaul : the Indian trilogy /
по: Mahanta, Namrata Rathore
Опубликовано: (2004)

Plants, genes, and crop biotechnology /
по: Chrispeels, Maarten J., 1938-
Опубликовано: (2003)

An interpretable deep learning approach to detect Alzheimer using MRI images
по: Oni, Farhan Anzum, и др.
Опубликовано: (2023)