CancerCare: A reliable and secured self-supervising and interactive system using deep learning

CancerCare: A reliable and secured self-supervising and interactive system using deep learning

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

Xehetasun bibliografikoak
Egile Nagusiak:	Khisa, Pushpakali, Hossain, Arisha, Raihana, Anika, Khan, Alisha, Tonu, Tamanna Sultana
Beste egile batzuk:	Noor, Jannatun
Formatua:	Thesis
Hizkuntza:	English
Argitaratua:	Brac University 2024
Gaiak:	Histopathological cell image Deep convolutional neural network VGG16 VGG19 ResNet50 ResNet152 Xception DenseNet12 Survey Image recognition Oncologists Cognitive learning theory (Deep learning)
Sarrera elektronikoa:	http://hdl.handle.net/10361/22059

Antzeko izenburuak

Citrus leaf disease detection by image processing
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Argitaratua: (2024)

Detection of coronary artery blockage at an early stage using effective deep learning technique
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Argitaratua: (2023)

Non-clinical Covid19 diagnosis on CT-scan, Chest X-ray, and respiratory patterns using deep-learning and signal processing
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Argitaratua: (2023)

Prediction of glaucoma from fundus images leveraging transfer learning in deep neural network
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Argitaratua: (2021)

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

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

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

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

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

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

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

Alzheimer’s Disease detection and classification using transfer learning techniques and ensembling operations on convolutional neural networks
nork: Awwal, Alvina, et al.
Argitaratua: (2021)

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

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

Unmasking malignancy of lung nodule using a modernized ConvNet toward the design of a vision transformer
nork: Reza, Jamil Ur, et al.
Argitaratua: (2023)

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

Cassava leaf disease classification using deep learning and convolutional neural network ensemble
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Argitaratua: (2022)

An Efficient deep learning approach to detect Brain Tumor using MRI images
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Argitaratua: (2022)

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

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

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

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

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

Violent activity detection through surveillance camera using deep learning
nork: Miah, Parvez, et al.
Argitaratua: (2023)

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

Explainable breast cancer detection from Histopathology images using transfer learning and XAI
nork: Farabi, Farhan, et al.
Argitaratua: (2023)

Early detection of cervical cancer using deep neural networks
nork: Akhund, Atoshi, et al.
Argitaratua: (2023)

An Analysis on Bengali handwritten conjunct character recognition and prediction
nork: Munawar, Maazin, et al.
Argitaratua: (2021)

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

An interpretable deep learning approach to detect Alzheimer using MRI images
nork: Oni, Farhan Anzum, et al.
Argitaratua: (2023)

Approaching transfer learning to identify correctly worn facial masks
nork: Sadid, Tausif, et al.
Argitaratua: (2021)

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

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

Classiﬁcation of damaged vegetation areas using convolutional neural network over satellite images
nork: Haque, Samiha, et al.
Argitaratua: (2021)

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

An efficient approach for recyclable waste detection and classification using image processing techniques
nork: Chowdhury, Prabal Kumar, et al.
Argitaratua: (2024)

Tomato leaf disease detection using convolutional neural network
nork: Hasan, Md. Riazul, et al.
Argitaratua: (2023)

Detection of pneumonia from chest X-ray images using machine learning
nork: Priya, Afsana Rahman, et al.
Argitaratua: (2023)

Detection of prodromal parkinson’s disease with fMRI data and deep neural network approaches
nork: Shahriar, Farhan, et al.
Argitaratua: (2021)

Deep learning-based waste classification system for efficient waste management
nork: Nakib, Abdullah Al, et al.
Argitaratua: (2022)