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Convolutional Networks Used to Classify Video and Audio Data
- Source :
- Research Papers. Faculty of Materials Science and Technology. Slovak University of Technology in Trnava, Vol 27, Iss 45, Pp 113-120 (2019)
- Publication Year :
- 2019
- Publisher :
- Sciendo, 2019.
-
Abstract
- Deep learning is a kind of machine learning, and machine learning is a kind of artificial intelligence. Machine learning depicts groups of various technologies, and deep learning is one of them. The use of deep learning is an integral part of the current data classification practice in today’s world. This paper introduces the possibilities of classification using convolutional networks. Experiments focused on audio and video data show different approaches to data classification. Most experiments use the well-known pre-trained AlexNet network with various pre-processing types of input data. However, there are also comparisons of other neural network architectures, and we also show the results of training on small and larger datasets. The paper comprises description of eight different kinds of experiments. Several training sessions were conducted in each experiment with different aspects that were monitored. The focus was put on the effect of batch size on the accuracy of deep learning, including many other parameters that affect deep learning [1].
- Subjects :
- 0209 industrial biotechnology
business.industry
Computer science
Deep learning
Speech recognition
020208 electrical & electronic engineering
convolutional neural network
deep learning
02 engineering and technology
Convolutional neural network
020901 industrial engineering & automation
audio-visual data
classification
0202 electrical engineering, electronic engineering, information engineering
alexnet
lcsh:TA401-492
lcsh:Materials of engineering and construction. Mechanics of materials
Artificial intelligence
business
Subjects
Details
- Language :
- English
- ISSN :
- 13380532
- Volume :
- 27
- Issue :
- 45
- Database :
- OpenAIRE
- Journal :
- Research Papers. Faculty of Materials Science and Technology. Slovak University of Technology in Trnava
- Accession number :
- edsair.doi.dedup.....31f15732bbd2f2db080158f5468e38b3