Journal Article10.9728/DCS.2020.21.3.445
AR based Beverage Information Visualization and Sharing System using Deep Learning
Jongin Choe,Junghyun Lee,Dongwan Kang,Sanghyun Seo +3 more
- 31 Mar 2020
- Vol. 21, Iss: 3, pp 445-452
About: The article was published on 31 Mar 2020. The article focuses on the topics: Information visualization.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Experimental Evaluation of Deep Learning Methods for an Intelligent Pathological Voice Detection System Using the Saarbruecken Voice Database
TL;DR: In this paper, the authors used deep learning methods, such as feedforward neural network (FNN) and convolutional neural network(CNN), for pathological voice detection using mel-frequency cepstral coefficients (MFCCs), linear prediction cepstrum coefficients (LPCCs) and higher-order statistics (HOSs) parameters.
25
Information visualization method for intelligent construction of prefabricated buildings based on P-ISOMAP algorithm
Xue Ouyang,Siyu Pan,Ping Ouyang +2 more
TL;DR: In this article , a case design and analysis of the information visualization of the intelligent construction of prefabricated buildings based on the P-ISOMAP algorithm and BIM technology is carried out.
8
Intelligent monitoring system for quality of life of colostomy patients based on deep learning and AR
Shengqin Wang,Yuqing Zhang,Fangfang Xu,Guihua Zhou +3 more
TL;DR: This study develops an intelligent monitoring system for colostomy patients using deep learning, augmented reality, and triple-technology integration, improving early warning performance, standardizing nursing operations, and reducing medical resource consumption through a data-driven approach.
References
Caffe: Convolutional Architecture for Fast Feature Embedding
Yangqing Jia,Evan Shelhamer,Jeff Donahue,Sergey Karayev,Jonathan Long,Ross Girshick,Sergio Guadarrama,Trevor Darrell +7 more
- 03 Nov 2014
TL;DR: Caffe provides multimedia scientists and practitioners with a clean and modifiable framework for state-of-the-art deep learning algorithms and a collection of reference models for training and deploying general-purpose convolutional neural networks and other deep models efficiently on commodity architectures.
Backpropagation applied to handwritten zip code recognition
Yann LeCun,Bernhard E. Boser,John S. Denker,D. Henderson,Richard Howard,W. Hubbard,Lawrence D. Jackel +6 more
TL;DR: This paper demonstrates how constraints from the task domain can be integrated into a backpropagation network through the architecture of the network, successfully applied to the recognition of handwritten zip code digits provided by the U.S. Postal Service.
12.5K
Recent advances in augmented reality
TL;DR: This work refers one to the original survey for descriptions of potential applications, summaries of AR system characteristics, and an introduction to the crucial problem of registration, including sources of registration error and error-reduction strategies.
4.5K
Visualizing Big Data with augmented and virtual reality: challenges and research agenda
TL;DR: A classification of existing data types, analytical methods, visualization techniques and tools, with a particular emphasis placed on surveying the evolution of visualization methodology over the past years is provided, and disadvantages of existing visualization methods are revealed.
Consumer participation in using online recommendation agents: effects on satisfaction, trust, and purchase intentions
TL;DR: In this article, the role of consumer participation in using online product recommendation agents (RAs) has been examined and it was shown that greater consumer participation leads to more satisfaction, greater trust, and higher purchase intentions, related to the RA and its recommendations.
249