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.

Bibliographische Detailangaben
Hauptverfasser:	Ruhi, Zurana Mehrin, Sheetal, Farahatul Aziz, Prithu, Farisha Hossain
Weitere Verfasser:	Arif, Hossain
Format:	Abschlussarbeit
Sprache:	en_US
Veröffentlicht:	Brac University 2021
Schlagworte:	CNN Residual Network Machine Learning XGboost Road Inspection Potholes Cracks
Online Zugang:	http://hdl.handle.net/10361/14359

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