.png){kind=icon}
返回
Fish age analysis and classification with kernel methods
.png){kind=icon}
PRE
AI
DOI：10.1016/j.patrec.2007.01.016.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
`Knowledge of age in fish populations is of great significance in stock assessment. Fishery scientists have traditionally used fish otoliths, i.e. calcified structures in the inner car to estimate fish age, because their shape changes during a fish's lifetime. However, many factors influence changes in otolith shape, sometimes in unpredictable ways, so manual classification remains a complex task that may yield inaccurate age estimations. Here, we discuss automatic pattern analysis and recognition for accomplishing this task and present a novel application of two well-known kernel methods: kernel principal component analysis and multi-class support vector machines for analyzing and classifying fish ages from otolith images. Significant results were achieved as a result of analyzing a cod otolith database. (C) 2007 Elsevier B.V. All rights reserved.
Keyword:
automated fish age classification
statistical learning
kernel principal component analysis
support vector machines
scientific applications of pattern recognition
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.3
论文数:
8.0K
被引数:
1.8W
机构
暂无机构信息
引用论文
Gradient-based learning applied to document recognition基于梯度的学习在文档识别中的应用.png)
PROCEEDINGS OF THE IEEE
PROCEEDINGS OF THE IEEEIF25.9
PREAI
分享收藏
查看更多内容