人工智能
计算机科学
卷积神经网络
人工神经网络
领域(数学)
机器学习
深度学习
简单(哲学)
新认知
模式识别(心理学)
时滞神经网络
数学
认识论
哲学
纯数学
作者
Keiron O’Shea,Ryan Nash
摘要
The field of machine learning has taken a dramatic twist in recent times, with the rise of the Artificial Neural Network (ANN). These biologically inspired computational models are able to far exceed the performance of previous forms of artificial intelligence in common machine learning tasks. One of the most impressive forms of ANN architecture is that of the Convolutional Neural Network (CNN). CNNs are primarily used to solve difficult image-driven pattern recognition tasks and with their precise yet simple architecture, offers a simplified method of getting started with ANNs. This document provides a brief introduction to CNNs, discussing recently published papers and newly formed techniques in developing these brilliantly fantastic image recognition models. This introduction assumes you are familiar with the fundamentals of ANNs and machine learning.
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