Deep learning-based hybrid multi-task model for adrenocortical carcinoma segmentation and classification

Deep learning-based hybrid multi-task model for adrenocortical carcinoma segmentation and classification

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2024.

Dettagli Bibliografici
Autori principali:	Datta, Nirjhor, Rashid, Md. Hasanur, Rahman, Samiur, Nodi, Naima Tahsin, Uddin, Moin
Altri autori:	Hossain, Muhammad Iqbal
Natura:	Tesi
Lingua:	English
Pubblicazione:	Brac University 2024
Soggetti:	Deep learning Convolutional neural network CNN Adrenocortical Carcinoma Disease detection Neural networks (Computer science) Deep learning (Machine learning) Computational intelligence
Accesso online:	http://hdl.handle.net/10361/22838

Documenti analoghi

Classification of peripheral blood cell images using deep learning
di: Aadi, Oyshik Ahmed, et al.
Pubblicazione: (2024)

Visual object classification from fMRI data
di: Newaz, Syed Mishar, et al.
Pubblicazione: (2022)

ProteoKnight: phage virion protein classification with CNN and uncertainty quantification
di: Bhuiyan, Abir Ahammed, et al.
Pubblicazione: (2024)

Diabetic retinopathy detection and classification by using deep learning
di: Hossain, Shahriar, et al.
Pubblicazione: (2022)

Analysis of transformer and CNN based approaches for classifying renal abnormality from image data
di: Reza, S. M. Mushfiq, et al.
Pubblicazione: (2024)

An efficient deep learning approach to detect skin Cancer
di: Islam, Ashfaqul, et al.
Pubblicazione: (2022)

Cancer classification using deep learning from medical image data
di: Monir, Raiyan Janik, et al.
Pubblicazione: (2022)

Skin cancer detection and classification using multiple optimized deep convolutional neural network
di: Sakir, Adnan, et al.
Pubblicazione: (2023)

Bangali Handwritten characters classification using Deep Convolutional Neural Network
di: Sikder, Shihab Uddin, et al.
Pubblicazione: (2022)

Automated detection of Malignant Lesions in the ovary using deep learning models and XAI
di: Ifty, Md. Hasin Sarwar, et al.
Pubblicazione: (2024)

Analysis of uncertainty in different neural network structures using monte carlo dropout
di: Islam, Md. Farhadul, et al.
Pubblicazione: (2024)

An efficient deep learning approach to detect skin cancer using image data
di: Chowdhury, Yaser Al Rahman, et al.
Pubblicazione: (2023)

Intracranial hemorrhage detection using CNN-LSTM fusion model
di: Ahmed, Kazi sabab, et al.
Pubblicazione: (2022)

An efficient ML approach to detect brain tumor using MRI images
di: Muktadir, MD. Arafat, et al.
Pubblicazione: (2024)

Classification of respiratory diseases and COVID-19 from respiratory and cough sound using deep learning techniques
di: Ahasan, Md. Mubtasim, et al.
Pubblicazione: (2022)

Early Schizophrenia Diagnosis with 3D Convolutional Neural Network
di: Ashraf, S.M. Nabil, et al.
Pubblicazione: (2021)

Analysis of uncertainty in different neural network structures using Monte Carlo Dropout
di: Islam, Md. Farhadul, et al.
Pubblicazione: (2024)

Corn leaf disease detection using deep convolution neural network
di: Rabbi, Rawhatur, et al.
Pubblicazione: (2023)

Visual object recognition using deep convolutional neural network
di: Ahmed, Sabbir
Pubblicazione: (2017)

Automatic brain tumor segmentation using U-ResUNet chain model approach
di: Alam, Mohd Tanjeem, et al.
Pubblicazione: (2022)

An efficient deep learning approach to classify white blood cells
di: Turja, Afif Ibna Kadir Khan, et al.
Pubblicazione: (2024)

Classification of retinal diseases from OCT images using deep learning models
di: Mokarrom, Md Saif, et al.
Pubblicazione: (2024)

Classification of different magnetic structures from image data using deep neural networks
di: Ibn Hasib, Fahad, et al.
Pubblicazione: (2023)

Plant leaf disease identification
di: Hasan Mahin, Mohammad Rakibul, et al.
Pubblicazione: (2024)

Bang-lish sentiment classification using deep learning
di: Saleheen, Abrar, et al.
Pubblicazione: (2023)

Efficient image processing and machine learning approach for predicting retinal diseases
di: Hasib, Mehadi Hasan, et al.
Pubblicazione: (2021)

Detection and classification of Mango Leaf diseases utilizing convolutional neural network models
di: Ferdous, Md.Rubaiat, et al.
Pubblicazione: (2024)

X-Ray classification to detect COVID-19 using ensemble model
di: Solaiman, Ishmam Ahmed, et al.
Pubblicazione: (2021)

Comparative analysis and implementation of credit risk prediction through distinct machine learning models
di: Turjo, Aquib Abtahi, et al.
Pubblicazione: (2021)

A conventional & deep learning strategy for analyzing & detecting Bengali fake news in online medium
di: Ahmed, Istiak, et al.
Pubblicazione: (2023)

An eﬃcient deep learning approach for detecting lung disease from chest X-ray images using transfer learning and ensemble modeling
di: Sagor, Mostofa Kamal, et al.
Pubblicazione: (2021)

BanglaBait: using transformers, neural networks & statistical classifiers to detect clickbaits in New Bangla Clickbait Dataset
di: Mahtab, Motahar, et al.
Pubblicazione: (2022)

Detection of handwritten text using convolutional neural network
di: Jasim, Rabib Bin, et al.
Pubblicazione: (2024)

Hybrid recommendation system of intelligent captioning using deep learning networks
di: Wasi, Ahamed Al, et al.
Pubblicazione: (2024)

Real time action recognition from video footage
di: Apon, Tasnim Sakib, et al.
Pubblicazione: (2021)

Cassava leaf disease classification using deep learning and convolutional neural network ensemble
di: Shahriar, Hasan, et al.
Pubblicazione: (2022)

Recall-Net: A CNN-based Model for Four-class Classification of Alzheimer’s Disease
di: Hasan, M. M. Kamrul, et al.
Pubblicazione: (2022)

Leveraging sequential deep learning models for detecting multitude of human action categories
di: Pranta, Kazi Al Refat, et al.
Pubblicazione: (2024)

Autonomous fault diagnosis of commercially available PV modules using high-end deep learning frameworks
di: Tasawar, Ihtyaz Kader, et al.
Pubblicazione: (2021)

Prostate cancer detection using deep learning neural network with transfer learning approach
di: Badhon, Ariful Islam Mahmud, et al.
Pubblicazione: (2022)