A Survey on Supervised Convolutional Neural Network and Its Major Applications

D. Mane, U. Kulkarni
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引用次数: 46

Abstract

With the advances in the computer science field, various new data science techniques have been emerged. Convolutional Neural Network (CNN) is one of the Deep Learning techniques which have captured lots of attention as far as real world applications are considered. It is nothing but the multilayer architecture with hidden computational power which detects features itself. It doesn't require any handcrafted features. The remarkable increase in the computational power of Convolutional Neural Network is due to the use of Graphics processor units, parallel computing, also the availability of large amount of data in various variety forms. This paper gives the broad view of various supervised Convolutional Neural Network applications with its salient features in the fields, mainly Computer vision for Pattern and Object Detection, Natural Language Processing, Speech Recognition, Medical image analysis.
有监督卷积神经网络及其主要应用综述
随着计算机科学领域的发展,出现了各种新的数据科学技术。卷积神经网络(CNN)是一种深度学习技术,在现实世界的应用中引起了广泛的关注。它只不过是具有隐藏计算能力的多层体系结构,它可以自己检测特征。它不需要任何手工制作的功能。卷积神经网络计算能力的显著提高是由于图形处理器单元的使用,并行计算,以及各种形式的大量数据的可用性。本文综述了有监督卷积神经网络在模式和目标检测、自然语言处理、语音识别、医学图像分析等领域的应用及其突出特点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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