Active Learning on Neural Networks through Interactive Generation of Digit Patterns and Visual Representation
Active Learning on Neural Networks through Interactive Generation of Digit Patterns and Visual Representation
复制标题
DOI：
10.1109/isec57711.2023.10402169
复制
发表时间：
2023-03
期刊：
影响因子：
--
通讯作者：
Dong H. Jeong;Jin-Hee Cho;Feng Chen;A. Jøsang;Soo-Yeon Ji
中科院分区：
文献类型：
--
作者：
Dong H. Jeong;Jin-Hee Cho;Feng Chen;A. Jøsang;Soo-Yeon Ji
人工神经网络（ANN）已被广泛用于分析各种数据并解决不同领域的问题。然而，神经网络（NN）多年来一直被认为是黑盒操作，因为它们的底层计算和含义是隐藏的。由于这种性质，用户在解释神经网络的底层机制以及使用它们的好处时常常面临困难。在本文中，为了提高用户对神经网络的认知和理解，设计了一个交互式学习系统来创建数字模式并实时识别 m。为了帮助用户清楚地理解数字模式（即 $0\sim 9$）的视觉差异及其与神经网络的结果，考虑集成可视化以在二维显示空间中呈现所有数字模式并支持多个用户交互。对多个数据集进行评估，以确定其对于主动学习的可用性。此外，在夏季研讨会期间，通过要求研讨会参与者使用该系统来管理非正式用户测试。
Artificial neural networks (ANNs) have been broadly utilized to analyze various data and solve different domain problems. However, neural networks (NNs) have been considered a black box operation for years because their underlying computation and meaning are hidden. Due to this nature, users often face difficulties in interpreting the underlying mechanism of the NNs and the benefits of using them. In this paper, to improve users’ karning and understanding of NNs, an interactive learning system is designed to create digit patterns and recognize the m in real time. To help users clearly understand the visual differences of digit patterns (i.e., $0\sim 9$) and their results with an NN, integrating visualization is considered to present all digit patterns in a two-dimensional display space with supporting multiple user interactions. An evaluation with multiple datasets is conducted to determine its usability for active learning In addition, informal user testing is managed during a summer workshop by asking the workshop participants to use the system.