Information Entropy Based Convolution Block Attention Module and Deep Learning with Application to Autonomous Driving Object Detection

Muqing Fang

Information Entropy Based Convolution Block Attention Module and Deep Learning with Application to Autonomous Driving Object Detection.

Rel. Luciano Lavagno. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2020

Abstract:	In the autonomous driving detects obstacles solution, on-board cameras are used to identify vehicles, pedestrians, traffic cones, etc. Provide assistance for autonomous driving tasks.
Relators:	Luciano Lavagno
Academic year:	2020/21
Publication type:	Electronic
Number of Pages:	66
Additional Information:	Tesi secretata. Fulltext non presente
Subjects:
Corso di laurea:	Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering)
Classe di laurea:	New organization > Master science > LM-32 - COMPUTER SYSTEMS ENGINEERING
Aziende collaboratrici:	Zongmu Technology Co.Ltd.
URI:	http://webthesis.biblio.polito.it/id/eprint/16003

Modify record (reserved for operators)