PlantGuard: intelligent plant disease detection

PlantGuard: intelligent plant disease detection

This project report is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2024.

Xehetasun bibliografikoak
Egile nagusia:	Khanom, Nazifa
Beste egile batzuk:	Hossain, Muhammad Iqbal
Formatua:	Project report
Hizkuntza:	English
Argitaratua:	Brac University 2024
Gaiak:	Leaf textures Texture features CNN Convolutional neural network Image data analysis Deep learning Disease detection Plant diseases > Diagnosis. Neural networks (Computer science) > Agricultural aspects. Artificial intelligence > Applications in agriculture.
Sarrera elektronikoa:	http://hdl.handle.net/10361/24033

Antzeko izenburuak

Plant leaf disease identification
nork: Hasan Mahin, Mohammad Rakibul, et al.
Argitaratua: (2024)

Detection and classification of Mango Leaf diseases utilizing convolutional neural network models
nork: Ferdous, Md.Rubaiat, et al.
Argitaratua: (2024)

Deep learning based early Glaucoma detection
nork: Islam, Aabrar, et al.
Argitaratua: (2024)

Leveraging deep learning algorithms for the timely detection of diseases in bean leaves
nork: Fiona, Driciru, et al.
Argitaratua: (2024)

Efficient image processing and machine learning approach for predicting retinal diseases
nork: Hasib, Mehadi Hasan, et al.
Argitaratua: (2021)

Tomato leaf disease detection using convolutional neural network
nork: Hasan, Md. Riazul, et al.
Argitaratua: (2023)

Pneumonia Disease detection using the convolutional neural network
nork: Ashrafee, Md. Iftid, et al.
Argitaratua: (2024)

Early detection of parkinson’s disease using image processing and artificial neural network
nork: Rumman, Mosarrat, et al.
Argitaratua: (2018)

Disease detection system of mango leaves
nork: Islam, Sabrina, et al.
Argitaratua: (2024)

Plant disease detection using convolutional neural network
nork: Hossain, Mohammad Shifat, et al.
Argitaratua: (2021)

Design and evaluation of convolutional neural network for detection of Alzheimer’s disease using MRI data
nork: Mahbub, Riasat, et al.
Argitaratua: (2022)

Automated system for detecting jute plant disease using image processing and machine learning integrated with mobile application
nork: Joyee, Faiza Nuzhat, et al.
Argitaratua: (2016)

Smart detection and classification of fungal disease in rice plants using image processing techniques
nork: Rashed, Akib, et al.
Argitaratua: (2024)

Incorporating deep features extracted from convolutional neural networks to utilize machine learning classifiers for improved identification of Maize Leaf Disease
nork: Khan, Shama, et al.
Argitaratua: (2024)

Autonomous fault diagnosis of commercially available PV modules using high-end deep learning frameworks
nork: Tasawar, Ihtyaz Kader, et al.
Argitaratua: (2021)

Automated detection of Malignant Lesions in the ovary using deep learning models and XAI
nork: Ifty, Md. Hasin Sarwar, et al.
Argitaratua: (2024)

A PSO-ANLBF based automated feature extraction method
nork: Shakhawat, Sabrina, et al.
Argitaratua: (2018)

Classification of Bangladeshi soil texture using convolutional neural network
nork: Raj, Hafiz Mohiuddin, et al.
Argitaratua: (2023)

An eﬃcient deep learning approach for detecting lung disease from chest X-ray images using transfer learning and ensemble modeling
nork: Sagor, Mostofa Kamal, et al.
Argitaratua: (2021)

Deep learning-based hybrid multi-task model for adrenocortical carcinoma segmentation and classification
nork: Datta, Nirjhor, et al.
Argitaratua: (2024)

Comparison of deep transfer learning models for cancer diagnosis
nork: Joya, Nadia Islam, et al.
Argitaratua: (2023)

Exploring machine learning techniques for symptom-based detection of livestock diseases
nork: Niloy, Mahir Ahmed, et al.
Argitaratua: (2024)

Traumatic meningeal enhancement detection by deep learning-based biomedical image analysis and handcrafted features extraction
nork: Uddin, Mohammad Sakib, et al.
Argitaratua: (2024)

Exploring Alzheimer's disease prediction with XAI in various neural network models
nork: Rahman, Quazi Ashikur, et al.
Argitaratua: (2022)

Enhanced medical image analysis: leveraging CUDA for fast and accurate Pneumonia detection with optimized CNNs
nork: Alvi, Md.Waseq Alauddin
Argitaratua: (2024)

An efficient deep learning approach for detecting Alzheimer’s disease using brain images
nork: Sani, Mehedi Hasan, et al.
Argitaratua: (2022)

Explainable AI (XAI) driven skin cancer detection using transformer and CNN based architecture
nork: Radiah, Faiza, et al.
Argitaratua: (2024)

Clustering and detection of good and bad rail line anchors from images
nork: Islam, Samiul, et al.
Argitaratua: (2017)

An efficient deep learning approach to detect skin Cancer
nork: Islam, Ashfaqul, et al.
Argitaratua: (2022)

Explainable Deepfake video detection using Convolutional Neural Network and CapsuleNet
nork: Ishrak, Gazi Hasin, et al.
Argitaratua: (2022)

Deep Learning based Medicinal Plants Leaf Recognition
nork: Mahalanabish, Tonusri
Argitaratua: (2023)

An interpretable diagnosis of retinal diseases using vision transformer and Grad-CAM
nork: Bhuiyan, Mahdi Hasan, et al.
Argitaratua: (2024)

Silent voice: harnessing deep learning for lip-reading in Bangla
nork: Shaheen, Munia, et al.
Argitaratua: (2024)

Skin cancer classification for seven types of skin lesions
nork: Rahman, Md. Tawsifur, et al.
Argitaratua: (2024)

Leaf classification by feature extraction using CNN
nork: Bhuiyan, Md. Mazharul Islam, et al.
Argitaratua: (2020)

Smart agriculture management system for rice disease detection and fertilizer
nork: Faiyaz, Md Abrar Hossen, et al.
Argitaratua: (2024)

Detecting Deepfake images using deep convolutional neural network
nork: Dhar, Arpita, et al.
Argitaratua: (2022)

Brain tumor detection with convolutional neural network
nork: Galib, Abrar Tahmid, et al.
Argitaratua: (2024)

An efficient deep learning approach for brain tumor detection using 3D convolutional neural network
nork: Ali, Syed Muaz
Argitaratua: (2023)

An efficient deep learning approach to detect neurodegenerative diseases using retinal images
nork: Irfanuddin, Chowdhury Mohammad, et al.
Argitaratua: (2023)