Efficient CNN Architecture for Multi-modal Aerial View Object Classification

被引：2
|
作者：
Miron, Casian [1 ]
Pasarica, Alexandru [1 ]
Timofte, Radu [1 ]
机构：
[1] Gheorghe Asachi Tech Univ, MCC Resources SRL, Iasi, Romania
来源：
2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW 2021 | 2021年
关键词：
D O I：
10.1109/CVPRW53098.2021.00068
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The NTIRE 2021 workshop features a Multi-modal Aerial View Object Classification Challenge. Its focus is on multi-sensor imagery classification in order to improve the performance of automatic target recognition (ATR) systems. In this paper we describe our entry in this challenge, a method focused on efficiency and low computational time, while maintaining a high level of accuracy. The method is a convolutional neural network with 11 convolutions, 1 max pooling layers and 3 residual blocks which has a total of 373.130 parameters. The method ranks 3rd in the Track 2 (SAR+EO) of the challenge.
引用
收藏
页码：560 / 565
页数：6
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