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.

Bibliografiska uppgifter
Huvudupphovsmän:	Ruhi, Zurana Mehrin, Sheetal, Farahatul Aziz, Prithu, Farisha Hossain
Övriga upphovsmän:	Arif, Hossain
Materialtyp:	Lärdomsprov
Språk:	en_US
Publicerad:	Brac University 2021
Ämnen:	CNN Residual Network Machine Learning XGboost Road Inspection Potholes Cracks
Länkar:	http://hdl.handle.net/10361/14359

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