Deep learning algorithms increasingly support automated systems in areas such as human activity recognition and purchase recommendation.We identify a current trend in which data is transformed first into abstract visu...Deep learning algorithms increasingly support automated systems in areas such as human activity recognition and purchase recommendation.We identify a current trend in which data is transformed first into abstract visualizations and then processed by a computer vision deep learning pipeline.We call this VisuaLization As Intermediate Representation(VLAIR)and believe that it can be instrumental to support accurate recognition in a number of fields while also enhancing humans’ability to interpret deep learning models for debugging purposes or for personal use.In this paper we describe the potential advantages of this approach and explore various visualization mappings and deep learning architectures.We evaluate several VLAIR alternatives for a specific problem(human activity recognition in an apartment)and show that VLAIR attains classification accuracy above classical machine learning algorithms and several other non-image-based deep learning algorithms with several data representations.展开更多
文摘Deep learning algorithms increasingly support automated systems in areas such as human activity recognition and purchase recommendation.We identify a current trend in which data is transformed first into abstract visualizations and then processed by a computer vision deep learning pipeline.We call this VisuaLization As Intermediate Representation(VLAIR)and believe that it can be instrumental to support accurate recognition in a number of fields while also enhancing humans’ability to interpret deep learning models for debugging purposes or for personal use.In this paper we describe the potential advantages of this approach and explore various visualization mappings and deep learning architectures.We evaluate several VLAIR alternatives for a specific problem(human activity recognition in an apartment)and show that VLAIR attains classification accuracy above classical machine learning algorithms and several other non-image-based deep learning algorithms with several data representations.
