卷积神经网络
计算机科学
联营
人工智能
反向传播
特征(语言学)
人气
深度学习
特征提取
人工神经网络
上下文图像分类
对象(语法)
模式识别(心理学)
机器学习
图像(数学)
社会心理学
心理学
哲学
语言学
作者
Arohan Ajit,Koustav Acharya,Abhishek Samanta
出处
期刊:2020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE)
日期:2020-02-01
被引量:325
标识
DOI:10.1109/ic-etite47903.2020.049
摘要
Before Convolutional Neural Networks gained popularity, computer recognition problems involved extracting features out of the data provided which was not adequately efficient or provided a high degree of accuracy. However in recent times, Convolutional Neural Networks have attempted to provide a higher level of efficiency and accuracy in all the fields in which it has been employed in most popular of which are Object Detection, Digit and Image Recognition. It employs a definitely algorithm of steps to follow including methods like Backpropagation, Convolutional Layers, Feature formation and Pooling. Also this article will also venture into use of various frameworks and tools that involve CNN model.
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