A comparison of deep learning U‐Net architectures for semantic segmentation on panoramic X-ray images

A comparison of deep learning U‐Net architectures for semantic segmentation on panoramic X-ray images

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

Bibliographische Detailangaben
Hauptverfasser:	Bin Mushfiq, Rahil, Zannah, Rafiatul, Bashar, Mubtasim, Alam, Md. Nafidul, Rahman, MD Aftabur
Weitere Verfasser:	Chakrabarty, Amitabha
Format:	Abschlussarbeit
Sprache:	English
Veröffentlicht:	Brac University 2024
Schlagworte:	Dental Semantic segmentation Data annotation OPG image U-net U-net variants Dice coefficient IoU Architecture comparison Deep learning (Machine learning) Cognitive learning theory (Deep learning)
Online Zugang:	http://hdl.handle.net/10361/22671

Ähnliche Einträge

Semantic segmentation with attention dense U-net for lung extraction from X-ray images
von: Auvy, Akib Al Mahmud, et al.
Veröffentlicht: (2023)

Image segmentation of X-Ray and optical images using U-Net/UNet++ based deep learning architecture
von: Sharma, Tanmoyee, et al.
Veröffentlicht: (2021)

Density based traffic control system for a four way intersection
von: Chowdhury, Faizul Bari, et al.
Veröffentlicht: (2024)

Ejection fraction estimation using deep semantic segmentation neural network on 2D Echocardiography data
von: Khan, Abde Musavvir, et al.
Veröffentlicht: (2021)

Semantic segmentation of tumor from 3D Structural MRI using U-Net Autoencoder
von: Farzana, Maisha, et al.
Veröffentlicht: (2021)

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

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

Myocardial infarction detection using ECG signal applying deep learning techniques - ConvNet, VGG16, InceptionV3 and MobileNet
von: Promita, Samanta Tabassum, et al.
Veröffentlicht: (2022)

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

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

A deep learning approach towards soft biometrics attributes prediction using CNN
von: Kibria, Maharab, et al.
Veröffentlicht: (2022)

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

Deep learning-based real-time pothole detection for avoiding road accident
von: Basher, Rafsan, et al.
Veröffentlicht: (2022)

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

U.S.-Berkeley launches 1st Bangladesh studies center in U.S.
von: IndiaWest
Veröffentlicht: (2015)

MoU between AIBS and BRACU
von: The Daily Star
Veröffentlicht: (2016)

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

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

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

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

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

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

A modern technique to detect potholes by Computer Vision and Deep Learning
von: Saif, Muntasir Mahmud, et al.
Veröffentlicht: (2023)

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

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

An active-learning based training-schedule for biomedical image segmentation on deep neural networks
von: Hassan, Mehadi, et al.
Veröffentlicht: (2021)

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

Deep learning-based hybrid multi-task model for adrenocortical carcinoma segmentation and classification
von: Datta, Nirjhor, et al.
Veröffentlicht: (2024)

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

Damaged road detection using Image Processing and Deep Learning
von: Swadesh, Shimran Mahbub, et al.
Veröffentlicht: (2022)

Brac University continues to support students amid pandemic
von: The Business Standard
Veröffentlicht: (2021)

Brac University ranks 3rd in University Rover Challenge
von: Dhaka Tribune
Veröffentlicht: (2020)

Banglalink signs MoU with Bracu to facilitate students’ skill development
von: Tribune Desk
Veröffentlicht: (2022)

BRAC University signs MoU with BFTI
von: The Financial Express
Veröffentlicht: (2022)

Application of CNN based architectures in detection of distracted drivers
von: Arafin, Irfana, et al.
Veröffentlicht: (2023)

Automated overtaking assistance system: a real-time approach using deep learning techniques
von: Moonjarin, Musarrat, et al.
Veröffentlicht: (2023)

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

U-net Based Autonomous Fetal Segmentation From 2D and 3D Ultrasound Images
von: Mithila, Maliha Tabassum, et al.
Veröffentlicht: (2022)

Skin disease detection and classification using deep learning
von: Shuvon, Mehedi Hasan, et al.
Veröffentlicht: (2022)

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