Poisonous Spider Recognition through Deep Learning

被引:0
作者
Yang, Donghan [1 ]
Ding, Xueyang [1 ]
Ye, Zhenyuan [1 ]
Sinnott, Richard O. [1 ]
机构
[1] Univ Melbourne, Sch Comp & Informat Syst, Melbourne, Vic, Australia
来源
PROCEEDINGS OF THE AUSTRALASIAN COMPUTER SCIENCE WEEK MULTICONFERENCE (ACSW 2020) | 2020年
关键词
Australian spiders; object detection; image classification; CNN; MobileNet; SSD; iPhone;
D O I
10.1145/3373017.3373031
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Deep learning and neural networks have recently gained considerable attention and are now one of the most popular topics in modern computer science. One of the most promising applications of deep learning is in the field of computer vision and especially in the application of convolutional neural networks (CNNs) for object detection and classification of images. In this paper, we explore various CNN models to identify and classify common species of spiders found in Australia with specific focus on poisonous spiders. We compare the accuracy and performance of the deep learning models on a range of diverse spider species. We also develop an iOS application as the front-end user application.
引用
收藏
页数:7
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