触手可及的深度学习

Jonathan Rogers, Dylan Simmons, Milesh Shah, Connor Rowland, Yi Shang
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引用次数: 2

摘要

从SurveyMonkey到Google Forms,在线调查已经成为现代研究的基石。然而,这些调查平台缺乏为研究人员提供高级分析的能力,通常需要昂贵的第三方分析软件来纠正它们的缺点。我们建议通过在现有的数据收集平台TigerAware上添加数据分析功能来解决这个问题。TigerAware提供了一个通用的、可定制的工具,允许没有技术专长的研究人员创建、管理和部署定制的移动调查。我们试图将数据分析功能添加到TigerAware平台,从基本的统计功能到通过深度学习的情感识别。我们的分析平台使用TigerAware收集的数据,在研究期间为研究人员提供实时分析。通过我们对TigerAware平台的补充,我们为研究人员提供了一种新颖的一体化工具,以促进有效的调查创建,调查管理,数据收集和数据分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deep Learning at Your Fingertips
From SurveyMonkey to Google Forms, online surveys have become a cornerstone of modern research. However, these survey platforms lack the ability to provide advanced analysis to researchers, often requiring expensive third-party analytics software to rectify their shortcomings. We propose to solve this problem by adding data analysis capabilities onto TigerAware, an existing data collection platform. TigerAware offers a generic and customizable tool which allows researchers without technical expertise to create, manage, and deploy custom mobile surveys to participants in real-time. We seek to add data analysis functionalities to the TigerAware platform ranging from basic statistics functions to emotion recognition via deep learning. Our analysis platform uses data collected by TigerAware to give researchers real-time analytics throughout the duration of their study. Through our additions to the TigerAware platform, we present a novel all-in-one tool for researchers to facilitate effective survey creation, survey administration, data collection, and data analysis.
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