A deep learning approach for pneumonia classiﬁcation from chest X-Ray images with ensemble modelling and explainable AI

A deep learning approach for pneumonia classiﬁcation from chest X-Ray images with ensemble modelling and explainable AI

This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2021.

Opis bibliograficzny
1. autor:	Akhter, Nasrin
Kolejni autorzy:	Alam, Md. Ashraful
Format:	Praca dyplomowa
Język:	English
Wydane:	Brac University 2023
Hasła przedmiotowe:	Pneumonia Chest x-ray Transfer learning Convolutional neural network VGG16 VGG19 ResNet50 ResNet101 Inception V3 PNEXAI Machine learning Artificial intelligence
Dostęp online:	http://hdl.handle.net/10361/21826

Podobne zapisy

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)

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

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

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

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

Detection of pneumonia from chest X-ray images using machine learning
od: Priya, Afsana Rahman, i wsp.
Wydane: (2023)

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

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

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

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

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

Detection of coronary artery blockage at an early stage using effective deep learning technique
od: Promit, Tahmid Ashrafee, 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)

Analyzing students’ concentration in online courses through Webcam
od: Asif, Md., i wsp.
Wydane: (2024)

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

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

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

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)

An efficient face recognition model using multiple angular images and deep neural network architecture
od: Subah, Silma, i wsp.
Wydane: (2024)

Skin lesion classification using different CNN models
od: Oli, Md. Yahea Sultan
Wydane: (2023)

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)

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

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

Thoracic complication detection on chest X-rays using deep learning
od: Ratul, Rizwanul Hoque, i wsp.
Wydane: (2021)

Cassava leaf disease classification using deep learning and convolutional neural network ensemble
od: Shahriar, Hasan, i wsp.
Wydane: (2022)

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

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

An Efficient deep learning approach to detect Brain Tumor using MRI images
od: Islam, Annur Tasnim, i wsp.
Wydane: (2022)

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

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

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

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

Explainable breast cancer detection from Histopathology images using transfer learning and XAI
od: Farabi, Farhan, i wsp.
Wydane: (2023)

Homomorphic encryption on deep learning in accurate prediction of brain tumour
od: Sarwar, Arafat, i wsp.
Wydane: (2023)

Detection of prodromal parkinson’s disease with fMRI data and deep neural network approaches
od: Shahriar, Farhan, i wsp.
Wydane: (2021)

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

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

Deep neural network models for COVID-19 diagnosis from CT-Scan, explainability and analysis using trained models
od: Islam, Tahsin, i wsp.
Wydane: (2021)

Skin cancer classification for seven types of skin lesions
od: Rahman, Md. Tawsifur, i wsp.
Wydane: (2024)

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