Deep neural network model construction with interactive code reuse and automatic code transformation

Abstract

Summary Many application developers have been recently interested in applying deep learning techniques to their works but have little knowledge and experience on them. This paper presents the methods for a GUI‐based modeling tool to easily build deep learning models and automatically transform them into executable program codes. For reuse of existing deep learning codes, it introduces a method that imports such a program code, extracts the deep learning model architecture, and transforms it into a graphical representation that can be modified on a graphical interface. Meanwhile, a deep learning model with many layers is difficult to be visualized on a small display screen. To handle the difficulty, it proposes a method to identify the submodules called articulable subgraphs in a deep learning model and to organize the deep learning model into a hierarchical architecture using the nesting relationships of articulable subgraphs. It introduces a method to identify frequent substractures as well as articulable subgraphs as building blocks for deep learning models for levelwise views. The hierarchical representation easily enables to build deep learning models with many layers. The GUI‐based modeling tool employing the proposed methods makes nonexpert developers easily use deep learning techniques in their practical applications.

[Retracted] Interactive Model of Rural Tourism and New Socialist Countryside Construction Using Deep Learning Technology

“…Hu puts forward that rural tourism refers to a new tourism business activity that provides sightseeing, leisure, vacation, experience, entertainment, and fitness for urban people through scientific planning, development, and design in rural areas, using rural natural environment, pastoral landscape, rural animal husbandry and fishery production, farming culture, folk culture, ancient towns and villages, and pleasant life [ 17 ]. Lee et al put forward that rural tourism can really show its significance only when it has made efforts and achieved results in protecting rural ecological environment, protecting cultural landscape and protecting ethnic customs, increasing enough employment opportunities, and driving local social and economic development at the same time [ 18 ]. Jaturapitpornchai et al put forward that the essence of rural tourism economic development is to use the beautiful natural environment and rich national culture to attract tourists and meet their growing tourism needs [ 19 ].…”

A Survey on Spiking Neural Networks

“…Deep neural networks (DNNs) have made great successes in various formerly difficult tasks such as vision, speech, natural language, and games [1][2][3][4][5]. They have many layers and parameters and thus require huge computing resources, resulting in high energy consumption.…”

Novel data mining paradigms based on soft computing and machine learning in the current and upcoming information society revolution

“…The paper “Deep neural network model construction with interactive code reuse and automatic code transformation” by Keon Myung Lee et al 15 presents a method to identify frequent substructures as well as articulable subgraphs as building blocks for deep learning models for levelwise views. The hierarchical representation easily enables to build deep learning models with many layers.…”