A comparative study of deep learning methods for automating road condition characterization

A comparative study of deep learning methods for automating road condition characterization

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2020.

Bibliografiske detaljer
Main Authors:	Ruhi, Zurana Mehrin, Sheetal, Farahatul Aziz, Prithu, Farisha Hossain
Andre forfattere:	Arif, Hossain
Format:	Thesis
Sprog:	en_US
Udgivet:	Brac University 2021
Fag:	CNN Residual Network Machine Learning XGboost Road Inspection Potholes Cracks
Online adgang:	http://hdl.handle.net/10361/14359

Lignende værker

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Udgivet: (2022)

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Udgivet: (2022)

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Udgivet: (2017)

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Udgivet: (2021)

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Brac University’s Social Impact Lab and Brac hold road safety workshop
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Udgivet: (2023)

Letter to City Corporation regarding road cleaning
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Udgivet: (2023)

Hate speech detection from social networking posts using CNN and XGBoost
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Udgivet: (2020)

An assessment of road safety knowledge of drivers and community: An impact evaluation of the project intervention
af: Saha, Polin Kumar
Udgivet: (2022)

Analysis of impact on IT personnel of outsourcing IT services in organization: a case study of procurement of IT services for “maintenance, upgradation and support services for BRTA-IS” in Bangladesh Road Transport Authority (BRTA)
af: Khalil, Md. Ibrahim
Udgivet: (2016)

Real time rail line anchor inspection : context of Bangladesh
af: Chowdhury, Omid
Udgivet: (2015)

Assessment of road safety awareness and knowledge among drivers and community people: A baseline study
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Udgivet: (2022)

A modern technique to detect potholes by Computer Vision and Deep Learning
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Udgivet: (2023)

Financial factors analysis for acquisition premium and anticipation using extreme gradient boosting and deep recurrent neural network
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Udgivet: (2020)

Road safety movement: Young adults and collective engagement in social movement
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Udgivet: (2023)

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Udgivet: (2016)

An intelligent road traffic management system
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Udgivet: (2016)

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Udgivet: (2022)

Preparation for the inspection visit to China
af: BUCG-ABC Joint Venture (BUCG-ABC JV)
Udgivet: (2023)

Early prediction of Alzheimer's disease using convolutional neural network
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Udgivet: (2020)

ব্র্যাক ইউনিভার্সিটির সেমিনারে বক্তারা: নতুন ব্যাংক প্রয়োজন নেই
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Udgivet: (2011)

Regarding inspection report of fire pump at BRACU NCP
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Udgivet: (2023)

A multimodal approach of sentiment analysis to predict customer emotions towards a product
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Udgivet: (2020)

Submitting inspection checklist for concreting, structural steel and other major works
af: Brac University
Udgivet: (2023)

Observation of BRACU on the test result and visual inspection report on the fire protection pipes and instruction to start the piping work immediately
af: Brac University
Udgivet: (2023)

Eve-teasing detection from video footage using computer vision and artificial intelligence
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Comparative study of toxic comments classification using machine learning algorithms
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Udgivet: (2021)

ResInvolution: an involution-ResNet fused global spatial relation leveraging model for histopathological image analysis under federated learning environment
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Udgivet: (2024)

A color vision approach considering weather conditions based on auto encoder techniques using deep neural networks
af: Raj, Mohammad Mainuddin, et al.
Udgivet: (2021)

Request to approve and release payment against assistance of inspecting work
af: BUCG-ABC Joint Venture
Udgivet: (2023)

The intuitionist /
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Udgivet: (2017)

TQM in Roads and Highways Department; Evaluate an approach-how it improves the performance of supply chain to its organization
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Udgivet: (2021)

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Udgivet: (2018)

Automatic braking system and smart safety features to avoid and reduce road accident
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Udgivet: (2022)

An improved deepfake detection using deep learning
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Udgivet: (2023)

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Udgivet: (2015)

Automatic helmet-less biker detection using deep learning
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Udgivet: (2024)

Deep learning-based waste classification system for efficient waste management
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Udgivet: (2022)