Image processing and deep learning approach to evaluate earthquake resistance of urban buildings

Image processing and deep learning approach to evaluate earthquake resistance of urban buildings

This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.

Bibliografiska uppgifter
Huvudupphovsmän:	Ahmed, Yasin, Alam, Tawsiful, Shakil, Md. Hasibur Rahman, Hossain, Md. Tanjidul
Övriga upphovsmän:	Alam, Dr. Md. Ashraful
Materialtyp:	Lärdomsprov
Språk:	English
Publicerad:	BRAC University 2018
Ämnen:	Earthquake Deep learning Image processing Machine learning Image processing > Digital techniques. Natural disasters.
Länkar:	http://hdl.handle.net/10361/11025

Liknande verk

Transfer learning based industrial steel plates fault diagnosis using industrial fault signals
av: Mizan, Mubasshira, et al.
Publicerad: (2024)

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

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

Detecting Deepfake images using deep convolutional neural network
av: Dhar, Arpita, et al.
Publicerad: (2022)

Structurally and semantically coherent deep image inpainting
av: Sami, Mirza Tanzim, et al.
Publicerad: (2019)

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

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

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

A study on earthquake preparedness in schools in Dhaka North city corporation
av: Ziauddin, Nafisa
Publicerad: (2017)

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

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

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

An efficient deep learning approach to detect citrus leaves disease
av: Emon, Shaharear Hossain, et al.
Publicerad: (2024)

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

Early stage detection and classification of colon cancer using deep learning and explainable AI on histopathological images
av: Hossain, Mainul, et al.
Publicerad: (2022)

Earthquake resistant design manual /
Publicerad: (2006)

Comparison of deep transfer learning models for cancer diagnosis
av: Joya, Nadia Islam, et al.
Publicerad: (2023)

Protovision: utilizing prototypical networks for retinal diseases classification based on few-shot learning
av: Nabil, Sheikh MD. Nafis Noor, et al.
Publicerad: (2024)

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

Traumatic meningeal enhancement detection by deep learning-based biomedical image analysis and handcrafted features extraction
av: Uddin, Mohammad Sakib, et al.
Publicerad: (2024)

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

Image processing based human detection and social distancing measurements with monitoring via fine tuned deep learning and computer vision
av: Datta, Anurag, et al.
Publicerad: (2022)

Role of the corporate sector in earthquake disaster: a case study of Dhaka city
av: Ferdous, Mushfequa
Publicerad: (2010)

A novel lightweight CNN approach for Bangladeshi sign language gesture recognition
av: Rahman, Aryan, et al.
Publicerad: (2023)

Image recognition by deep learning
av: Mohiuddin, Karishma, et al.
Publicerad: (2018)

An efficient deep learning approach to detect neurodegenerative diseases using retinal images
av: Irfanuddin, Chowdhury Mohammad, et al.
Publicerad: (2023)

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

Analysis of deep learning models on low-light pest detection
av: Irtiza, Md. Samin, et al.
Publicerad: (2023)

An efficient deep learning approach for detecting Alzheimer’s disease using brain images
av: Sani, Mehedi Hasan, et al.
Publicerad: (2022)

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

Full stack development of UBERA system
av: An Noor, Akib
Publicerad: (2024)

Monitoring of endangered fish using image processing and AI tools
av: Hossain, Naheen, et al.
Publicerad: (2019)

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

Detection of common thorax diseases from X-Ray images using a fusion of transfer and statistical learning method
av: Rafi, Ahmad Abdur, et al.
Publicerad: (2023)

Detection of multiple sclerosis using deep learning
av: Jannat, Sabila Al, et al.
Publicerad: (2021)

Generation of realistic images from human drawn sketches using deep learning
av: Mahbub, Mohammed Julfikar Ali, et al.
Publicerad: (2022)

Utilizing deep learning architectures for early detection of lung diseases in chest X-ray images
av: Ahmed, Sarder Tanvir, et al.
Publicerad: (2024)

Real time dynamic facial recognition of subject at motion using angular image
av: Tasneem, Sharah, et al.
Publicerad: (2024)

RetinalNet-500: a newly developed CNN model for eye disease detection
av: Toki, Sadikul Alim, et al.
Publicerad: (2023)

In-depth analysis of deep learning architectures for brain tumor classification in MRI scans
av: Haque, Hossain MD. Hasibul, et al.
Publicerad: (2024)