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Poisonous Spider Recognition through Deep Learning

Authors :
Zhenyuan Ye
Xueyang Ding
Donghan Yang
Richard O. Sinnott
Source :
ACSW
Publication Year :
2020
Publisher :
ACM, 2020.

Abstract

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.

Details

Database :
OpenAIRE
Journal :
Proceedings of the Australasian Computer Science Week Multiconference
Accession number :
edsair.doi...........ecff929539a2bd8ebe09c2551ecd5e5a
Full Text :
https://doi.org/10.1145/3373017.3373031