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- Author: Anonym
- Publisher: GRIN Verlag
- Year: 2020
- Pages: 32
- ISBN-10: 3346213080
- ISBN-13: 9783346213082
- Format: 14.8 x 21 x 0.2 cm, minkšti viršeliai
- Language: English
- SAVE -10% with code: EXTRA
The Architecture of Convnets and Data Processing. Advantages of Convolutional Neural Networks (e-book) (used book) | bookbook.eu
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Essay from the year 2020 in the subject Mathematics - Miscellaneous, grade: 1,3, University of Ulm, language: English, abstract: In the past two decades in particular, artificial neural networks have led to new approaches and processes in machine learning in many areas. They have replaced many existing processes. In some areas, they even exceed human performance. Impressive progress has been made in the area of image recognition and classification. Above all, this includes the introduction of convolutional neural networks (ConvNets). They belong to the class of neural networks. The first ConvNet was developed by LeCun et al. in 1989. ConvNets were especially developed to enhance image processing. Therefore, they provide a unique architecture. Due to their structure and functionality, ConvNets are particularly well suited within this field of application compared to other methods.
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- Author: Anonym
- Publisher: GRIN Verlag
- Year: 2020
- Pages: 32
- ISBN-10: 3346213080
- ISBN-13: 9783346213082
- Format: 14.8 x 21 x 0.2 cm, minkšti viršeliai
- Language: English English
Essay from the year 2020 in the subject Mathematics - Miscellaneous, grade: 1,3, University of Ulm, language: English, abstract: In the past two decades in particular, artificial neural networks have led to new approaches and processes in machine learning in many areas. They have replaced many existing processes. In some areas, they even exceed human performance. Impressive progress has been made in the area of image recognition and classification. Above all, this includes the introduction of convolutional neural networks (ConvNets). They belong to the class of neural networks. The first ConvNet was developed by LeCun et al. in 1989. ConvNets were especially developed to enhance image processing. Therefore, they provide a unique architecture. Due to their structure and functionality, ConvNets are particularly well suited within this field of application compared to other methods.
Reviews