Detection of pneumonia from chest X-ray images using machine learning

Detection of pneumonia from chest X-ray images using machine learning

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

Bibliografiske detaljer
Main Authors:	Priya, Afsana Rahman, Sarkar, Kashmira, Khan, Tania Rahman, Turna, Sohani Fatehin, Mubashshira, Sadia
Andre forfattere:	Karim, Dewan Ziaul
Format:	Thesis
Sprog:	English
Udgivet:	Brac University 2023
Fag:	X-ray images Computer-based algorithm Customized CNN model Pre-trained models VGG-16 Inceptionv3 ResNet50 VGG-19 Accuracy F1-Score Machine learning Neural networks (Computer science)
Online adgang:	http://hdl.handle.net/10361/22011

Lignende værker

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

Detecting brain tumor using deep neural networks from MRI images
af: Imamuzzaman, A.S.M., et al.
Udgivet: (2021)

Covid-19 infected lung detection using machine learning
af: Islam, Md. Muntaha, et al.
Udgivet: (2022)

Non-clinical Covid19 diagnosis on CT-scan, Chest X-ray, and respiratory patterns using deep-learning and signal processing
af: Tasnim, Sadia, et al.
Udgivet: (2023)

Bone age comparison using convolutional neural network
af: Nawaz, Fariha, et al.
Udgivet: (2019)

Analyzing students’ concentration in online courses through Webcam
af: Asif, Md., et al.
Udgivet: (2024)

CancerCare: A reliable and secured self-supervising and interactive system using deep learning
af: Khisa, Pushpakali, et al.
Udgivet: (2024)

Identifying brain abnormalities using image processing and CNN models
af: Talukder, Ismat Shehrin, et al.
Udgivet: (2021)

Two dimensional convolutional neural network CNN approach for detection of Bangla sign language
af: Nag, Pollock, et al.
Udgivet: (2023)

An efficient face recognition model using multiple angular images and deep neural network architecture
af: Subah, Silma, et al.
Udgivet: (2024)

An efficient deep learning approach to detect retinal disease using optical coherence tomographic images
af: Khan, Farhan Sakib, et al.
Udgivet: (2022)

Deep learning based automated diagnosis of Ocular Toxoplasmosis in fundus images using convolutional neural network
af: Choudhury, Prionto Kumar, et al.
Udgivet: (2024)

Prediction of glaucoma from fundus images leveraging transfer learning in deep neural network
af: Ismail, Sayem Mohammad, et al.
Udgivet: (2021)

Citrus leaf disease detection by image processing
af: Chowdhury, Mahir Faisal, et al.
Udgivet: (2024)

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

Detection of intracranial hemorrhage on CT scan images using convolutional neural network
af: Rahman, Afridi Ibn, et al.
Udgivet: (2022)

Kidney Disease detection and classification from CT Images using Watershed Segmentation and Deep Learning.
af: Hossain, Mohammad Sakib, et al.
Udgivet: (2023)

Retinal Diseases Detection using Deep Learning
af: Mashfi, Shahriar, et al.
Udgivet: (2023)

Enhancing eye disease classification through synergistic deep learning approaches
af: Rahaman, Asif, et al.
Udgivet: (2024)

Thoracic complication detection on chest X-rays using deep learning
af: Ratul, Rizwanul Hoque, et al.
Udgivet: (2021)

Crystals, x-rays and proteins
af: Sherwood, Dennis

Automatic waste classification using deep learning and computer vision techniques
af: Akash, MD., et al.
Udgivet: (2023)

Homomorphic encryption on deep learning in accurate prediction of brain tumour
af: Sarwar, Arafat, et al.
Udgivet: (2023)

Detection of Parkinson’s disease from Neuro-imagery using deep neural network with transfer learning
af: Asaduzzaman, et al.
Udgivet: (2021)

RansomListener: Ransom call sound investigation using LSTM and CNN Architectures
af: Rahman, Rafeed, et al.
Udgivet: (2021)

EAI4CC: deciphering lung and colon cancer categorization within a federated learning framework harnessing the power of explainable artificial intelligence
af: Mim, Ankhi Akter, et al.
Udgivet: (2024)

Detection of coronary artery blockage at an early stage using effective deep learning technique
af: Promit, Tahmid Ashrafee, et al.
Udgivet: (2023)

A deep learning approach to depression detection based on Convolutional Neural Networks and Transfer Learning
af: Sarmi, Kaniz Fatima, et al.
Udgivet: (2022)

Critical retinal disease detection from optical coherence tomography images by deep convolutional neural network and explainable machine learning
af: Datta, Pranab, et al.
Udgivet: (2021)

A domain and noise adversarial bird tune classification pipeline using deep neural network
af: Riya, Aparna Sarker, et al.
Udgivet: (2023)

Deep neural network models for COVID-19 diagnosis from CT-Scan, explainability and analysis using trained models
af: Islam, Tahsin, et al.
Udgivet: (2021)

MalFam: a comprehensive study on malware families with state-of-the-art CNN architectures with classifications and XAI
af: Haque, Abid Hossain, et al.
Udgivet: (2024)

Multi-classification Network for Detecting Skin Diseases using Deep Learning and XAI
af: Athina, Fahima Hasan, et al.
Udgivet: (2022)

Elements of x-ray diffraction /
af: Cullity, B. D. (Bernard Dennis)
Udgivet: (2002)

An efficient approach to detect melanoma skin cancer using a custom CNN model
af: Rahman, K.M Saidur, et al.
Udgivet: (2023)

A comparative study of lung cancer prediction using deep learning
af: Mugdho, Aka Mohammad, et al.
Udgivet: (2023)

Leveraging robust CNN architectures for real-time object recognition from conveyor belt
af: Moon, Nowrin Tasnim, et al.
Udgivet: (2023)

Speech command classification based on deep neural networks
af: Hossain, Md. Sakib, et al.
Udgivet: (2023)

Towards devising an effective and reliable means of fish detection and classification through the exploration of various deep learning algorithms
af: Farhan, Rafid, et al.
Udgivet: (2024)

Deep Learning based Bangla Voice to Braille Character Conversion System
af: Iqbal, Syed Bayes, et al.
Udgivet: (2022)