Disease detection system of mango leaves

Disease detection system of mango leaves

This final year design project is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2023.

Bibliografiske detaljer
Main Authors:	Islam, Sabrina, Paul, Apurba, Chowdhury, Oishe Roy, Fiza, Fahmida Akhter
Andre forfattere:	Department of Electrical and Electronic Engineering, Brac University
Format:	Project report
Sprog:	English
Udgivet:	Brac University 2024
Fag:	Agricultural robotics Image processing Disease detection Mango leaves pest Artificial intelligence > Agricultural applications. Plant diseases.
Online adgang:	http://hdl.handle.net/10361/22682

Lignende værker

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

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

PlantGuard: intelligent plant disease detection
af: Khanom, Nazifa
Udgivet: (2024)

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

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

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

Literature review of insect pests and diseases of rice in Bangladesh.
Udgivet: (1977)

An efficient deep learning approach to detect citrus leaves disease
af: Emon, Shaharear Hossain, et al.
Udgivet: (2024)

বাংলাদেশের কৃষির অনিষ্টকারী পোকামাকড় জীবনবৃত্তান্ত ও নিয়ন্ত্রণ / দ্বিতীয় খন্ড

Design of a smart photovoltaic greenhouse with plant growth based Monitoring System
af: Islam, MD Jubydul, et al.
Udgivet: (2024)

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

Machine learning approach for ECG analysis and predicting different heart diseases
af: Tithi, Sushmita Roy, et al.
Udgivet: (2019)

শস্যের রোগ /
af: আশরাফউজ্জামান, হাসান
Udgivet: (2001)

Comparison of machine learning techniques to predict cardiovascular disease
af: Jaber, Mir Mohammad, et al.
Udgivet: (2019)

The role of Artificial Intelligence (AI) in the detection and diagnosis of chronic diseases – a review
af: Zaman, Mumtahina
Udgivet: (2022)

Maternity leave: (A study of its impact on female employees in organisations in Dhaka Bangladesh)
af: Chowdhury, Shaan Ahmed
Udgivet: (2023)

Comparative analysis of machine learning models for the prediction of asthma disease among the cardiovascular disease patients
af: Jahan, Asif
Udgivet: (2024)

A deep neural network approach for intelligent crop selection and yield prediction based on 46 parameters for agricultural zone-28 in Bangladesh
af: Islam, Tanhim, et al.
Udgivet: (2018)

Friends of the rice farmer : helpful insects, spiders, and pathogens /
af: Shepard, Barclay M.
Udgivet: (1987)

Investigation of in-vitro antioxidant and cytotoxic potential of Crotalaria pallida leaves
af: Probha, Nafisa Shama
Udgivet: (2018)

আম /
af: সিদ্দিকী, মাহবুব

Evaluating CNN and Vvsion transformer models for Mango Leaf variety identification
af: Labiba, Zaima, et al.
Udgivet: (2024)

Quantitative determination of artificial sweeteners and sucrose in energy drinks and mango juice available in Dhaka city by UV-Spectrophotometric method
af: Kanon, Kabirul Islam
Udgivet: (2018)

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

Studies on physico-chemical and microbiological qualities of some selected brand of mango fruit juice of Bangladesh
af: Amin, Md. Ruhul
Udgivet: (2016)

An Analysis of effectiveness of Banglalink’s leave policy
af: Abir, Md. Bashiur Rahman
Udgivet: (2015)

A semi-supervised federated learning approach leveraging pseudo-labeling for Knee Osteoarthritis severity detection
af: Rifat, Rakib Hossain
Udgivet: (2024)

Demystify the blackbox model of automated detection of lung and kidney diseases from X-ray and CT radiographs
af: Islam, Md. Nazmul
Udgivet: (2023)

Real time performance analysis on DDoS attack detection using machine learning
af: Suvra, Debashis Kar, et al.
Udgivet: (2021)

Multimodal human detection in disaster situations using deep learning & artificial intelligence
af: Rafat, Md. Tasbi, et al.
Udgivet: (2023)

Emerging therapies of Alzheimer’s disease: a comprehensive review
af: Tasin, Md Abtahi
Udgivet: (2023)

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

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

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

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

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

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

Bengali hand sign language recognition using convolutional neural networks
af: Rumi, Roisul Islam, et al.
Udgivet: (2019)

Deepfake detection using neural networks
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Udgivet: (2021)

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