Machine fault diagnosis using a modified transferable CNN

Machine fault diagnosis using a modified transferable CNN

This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2023.

Opis bibliograficzny
1. autor:	Shammi, Sanjana Khan
Kolejni autorzy:	Chakraborty, Amitabha
Format:	Praca dyplomowa
Język:	English
Wydane:	Brac University 2024
Hasła przedmiotowe:	Transfer learning CNN ResNet18 Leaky ReLU XAI SqueezeNet Fault location (Engineering) > Automation. Machine learning.
Dostęp online:	http://hdl.handle.net/10361/22650

Podobne zapisy

A Comparative study on Bengali handwritten character recognition and prediction using CNN
od: Abrar, Muntaqa, i wsp.
Wydane: (2021)

A domain and noise adversarial bird tune classification pipeline using deep neural network
od: Riya, Aparna Sarker, i wsp.
Wydane: (2023)

Non-clinical Covid19 diagnosis on CT-scan, Chest X-ray, and respiratory patterns using deep-learning and signal processing
od: Tasnim, Sadia, i wsp.
Wydane: (2023)

Multi-classification Network for Detecting Skin Diseases using Deep Learning and XAI
od: Athina, Fahima Hasan, i wsp.
Wydane: (2022)

A comparative study of lung cancer prediction using deep learning
od: Mugdho, Aka Mohammad, i wsp.
Wydane: (2023)

Citrus leaf disease detection by image processing
od: Chowdhury, Mahir Faisal, i wsp.
Wydane: (2024)

A descriptive study on development of a transfer learning based fault detection model using 2D CNN for air compressors
od: Hasan, Moenul, i wsp.
Wydane: (2021)

Detection of coronary artery blockage at an early stage using effective deep learning technique
od: Promit, Tahmid Ashrafee, i wsp.
Wydane: (2023)

CancerCare: A reliable and secured self-supervising and interactive system using deep learning
od: Khisa, Pushpakali, i wsp.
Wydane: (2024)

EAI4CC: deciphering lung and colon cancer categorization within a federated learning framework harnessing the power of explainable artificial intelligence
od: Mim, Ankhi Akter, i wsp.
Wydane: (2024)

Kidney Disease detection and classification from CT Images using Watershed Segmentation and Deep Learning.
od: Hossain, Mohammad Sakib, i wsp.
Wydane: (2023)

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

Covid-19 infected lung detection using machine learning
od: Islam, Md. Muntaha, i wsp.
Wydane: (2022)

MalFam: a comprehensive study on malware families with state-of-the-art CNN architectures with classifications and XAI
od: Haque, Abid Hossain, i wsp.
Wydane: (2024)

Alzheimer’s Disease detection and classification using transfer learning techniques and ensembling operations on convolutional neural networks
od: Awwal, Alvina, i wsp.
Wydane: (2021)

Identifying brain abnormalities using image processing and CNN models
od: Talukder, Ismat Shehrin, i wsp.
Wydane: (2021)

Plant disease detection using convolutional neural network
od: Hossain, Mohammad Shifat, i wsp.
Wydane: (2021)

Unmasking malignancy of lung nodule using a modernized ConvNet toward the design of a vision transformer
od: Reza, Jamil Ur, i wsp.
Wydane: (2023)

Deep learning based automated diagnosis of Ocular Toxoplasmosis in fundus images using convolutional neural network
od: Choudhury, Prionto Kumar, i wsp.
Wydane: (2024)

Violent activity detection through surveillance camera using deep learning
od: Miah, Parvez, i wsp.
Wydane: (2023)

Detection of intracranial hemorrhage on CT scan images using convolutional neural network
od: Rahman, Afridi Ibn, i wsp.
Wydane: (2022)

An Analysis on Bengali handwritten conjunct character recognition and prediction
od: Munawar, Maazin, i wsp.
Wydane: (2021)

FoodieCal: a convolutional neural network based food detection and calorie estimation system
od: Mashraf, Chowdhury Zerif, i wsp.
Wydane: (2021)

Detecting brain tumor using deep neural networks from MRI images
od: Imamuzzaman, A.S.M., i wsp.
Wydane: (2021)

Fault detection in waste water treatment plant using statistical analysis & machine learning
od: Haque, Md. Ezazul, i wsp.
Wydane: (2019)

Bone age comparison using convolutional neural network
od: Nawaz, Fariha, i wsp.
Wydane: (2019)

Deep learning-based waste classification system for efficient waste management
od: Nakib, Abdullah Al, i wsp.
Wydane: (2022)

Fault analysis in solar photovoltaic arrays
od: Nunneh, Bill N.
Wydane: (2023)

Masked face identification using face recognition
od: Hossen, Tareq, i wsp.
Wydane: (2024)

Classiﬁcation of damaged vegetation areas using convolutional neural network over satellite images
od: Haque, Samiha, i wsp.
Wydane: (2021)

Prediction of glaucoma from fundus images leveraging transfer learning in deep neural network
od: Ismail, Sayem Mohammad, i wsp.
Wydane: (2021)

An efficient deep learning approach to detect retinal disease using optical coherence tomographic images
od: Khan, Farhan Sakib, i wsp.
Wydane: (2022)

Tomato leaf disease detection using Resnet-50 and MobileNet Architecture
od: Tahamid, Abu
Wydane: (2021)

Brain tumor segmentation from MRI images using convolutional neural networks
od: Khan, Mushfiqur Rahman
Wydane: (2024)

A deep learning approach to depression detection based on Convolutional Neural Networks and Transfer Learning
od: Sarmi, Kaniz Fatima, i wsp.
Wydane: (2022)

Leveraging robust CNN architectures for real-time object recognition from conveyor belt
od: Moon, Nowrin Tasnim, i wsp.
Wydane: (2023)

Speech command classification based on deep neural networks
od: Hossain, Md. Sakib, i wsp.
Wydane: (2023)

Tomato leaf disease detection using convolutional neural network
od: Hasan, Md. Riazul, i wsp.
Wydane: (2023)

A texture based industrial fault diagnosis model using Gammatone Filter Bank and transfer learning
od: Morshed, Atique, i wsp.
Wydane: (2021)

Approaching transfer learning to identify correctly worn facial masks
od: Sadid, Tausif, i wsp.
Wydane: (2021)