基于对象识别的深度学习性能改进

Shouket Abdulrahman Ahmed, H. Desa, A. T. T. Hussain
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引用次数: 0

摘要

深度学习结合了许多隐藏层和更根深蒂固的组合,平均人工神经网络(ANN),在学习算法中产生更精细、性能更好的自主性。大量的文献详细介绍和改进了深度学习相关的方法及其多年来的改进以及它们在使用中的适用性。然而,文献综述的主要焦点不是这些技术的使用,因此在深入研究预期的应用程序之前,将对这些机制进行简要概述
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance Improvements Using Deep Learning Based Object-Identification
Deep Learning incorporates numerous hidden layers and more rooted combinations that average Artificial Neural Networks (ANN), to produce more refined and better performing autonomy in learning algorithms. An incredible volume of literature details and improves upon Deep Learning related methods and their improvement through the years as well as their suitability in uses. Nevertheless, the primary focus of the literature review is not the enlistment of these techniques hence a concise overview will be provided over the mechanisms before delving into the intended applications
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