Autonomous fault diagnosis of commercially available PV modules using high-end deep learning frameworks

Autonomous fault diagnosis of commercially available PV modules using high-end deep learning frameworks

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2021.

Manylion Llyfryddiaeth
Prif Awduron:	Tasawar, Ihtyaz Kader, Tanzeem, Abyaz Kader, Ahmed, Tahmid, Zarin, Shah Faiza
Awduron Eraill:	Rahman, Md. Mosaddequr
Fformat:	Traethawd Ymchwil
Iaith:	English
Cyhoeddwyd:	Brac University 2021
Pynciau:	Deep Neural Network Convolutional Neural Network Infrared Image Processing Photovoltaic Cell Fault Diagnosis Hotspot Detection Deep Learning
Mynediad Ar-lein:	http://hdl.handle.net/10361/15153

Eitemau Tebyg

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Fault analysis in solar photovoltaic arrays
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Early Schizophrenia Diagnosis with 3D Convolutional Neural Network
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A texture based industrial fault diagnosis model using Gammatone Filter Bank and transfer learning
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Visual object recognition using deep convolutional neural network
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Analysis of uncertainty in different neural network structures using monte carlo dropout
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Comparative data analysis of a PV module system considering weather parameters
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Efficient image processing and machine learning approach for predicting retinal diseases
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An in depth analysis of neural network with application in finance
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A color vision approach considering weather conditions based on auto encoder techniques using deep neural networks
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Analysis of transformer and CNN based approaches for classifying renal abnormality from image data
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Comparison of deep transfer learning models for cancer diagnosis
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Accelerating 2d fault diagnosis of an induction motor using a graphics processing unit
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A color vision approach based on the autoencoder technique and deep neural networks for reconstructing color images under various lighting conditions
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Acoustic emission sensor network based fault diagnosis of induction motors using a gabor filter and multiclass support vector machines
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Analysis of uncertainty in different neural network structures using Monte Carlo Dropout
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A color vision approach for reconstructing color images in different lighting conditions based on auto encoder technique using deep neural networks
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Pneumonia Disease detection using the convolutional neural network
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Classification of peripheral blood cell images using deep learning
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Early detection of cervical cancer using deep neural networks
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Deep learning-based hybrid multi-task model for adrenocortical carcinoma segmentation and classification
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Automated detection of Malignant Lesions in the ovary using deep learning models and XAI
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Visual object classification from fMRI data
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Deep learning based automated diagnosis of Ocular Toxoplasmosis in fundus images using convolutional neural network
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A comparative study and performance analysis of poly and mono Si photovoltaic modules
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ProteoKnight: phage virion protein classification with CNN and uncertainty quantification
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An efficient ML approach to detect brain tumor using MRI images
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A deep learning approach for prediction of ADHD using brain structure
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An interpretable diagnosis of retinal diseases using vision transformer and Grad-CAM
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Segmentation based Kidney Tumor Classification using Deep Neural Network
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Leveraging deep learning algorithms for the timely detection of diseases in bean leaves
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An efficient deep learning approach for brain tumor detection using 3D convolutional neural network
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Classification of different magnetic structures from image data using deep neural networks
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An efficient deep learning approach to detect skin cancer using image data
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Diabetic retinopathy detection and classification by using deep learning
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