FACIAL RECOGNITION WITH MACHINE LEARNING
The development of the times and information and communication technology leads us to a surge of data. The work of processing extraordinary amount of data is very suitable given to the machine. But the ability of machine analysis is very low when compared with humans. We are interested to ᤙ...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/27419 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
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id-itb.:274192018-06-07T14:23:32ZFACIAL RECOGNITION WITH MACHINE LEARNING JANS (NIM: 10114073), FRITZ Indonesia Final Project INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/27419 The development of the times and information and communication technology leads us to a surge of data. The work of processing extraordinary amount of data is very suitable given to the machine. But the ability of machine analysis is very low when compared with humans. We are interested to find a way for the machine to learn the data provided by the user. We build artificial neural network structures that mimic the workings of human nerves. Then we find a way to connect data with output. Using the optimization technique we create a backward propagation algorithm that can improve the relationship between values in artificial neural networks. The structure is then tested to work on simple problems ranging from solving equations, recognizing handwritten digit and ultimately capable of distinguishing the human face text |
| institution |
Institut Teknologi Bandung |
| building |
Institut Teknologi Bandung Library |
| continent |
Asia |
| country |
Indonesia Indonesia |
| content_provider |
Institut Teknologi Bandung |
| collection |
Digital ITB |
| language |
Indonesia |
| description |
The development of the times and information and communication technology leads us to a surge of data. The work of processing extraordinary amount of data is very suitable given to the machine. But the ability of machine analysis is very low when compared with humans. We are interested to find a way for the machine to learn the data provided by the user. We build artificial neural network structures that mimic the workings of human nerves. Then we find a way to connect data with output. Using the optimization technique we create a backward propagation algorithm that can improve the relationship between values in artificial neural networks. The structure is then tested to work on simple problems ranging from solving equations, recognizing handwritten digit and ultimately capable of distinguishing the human face |
| format |
Final Project |
| author |
JANS (NIM: 10114073), FRITZ |
| spellingShingle |
JANS (NIM: 10114073), FRITZ FACIAL RECOGNITION WITH MACHINE LEARNING |
| author_facet |
JANS (NIM: 10114073), FRITZ |
| author_sort |
JANS (NIM: 10114073), FRITZ |
| title |
FACIAL RECOGNITION WITH MACHINE LEARNING |
| title_short |
FACIAL RECOGNITION WITH MACHINE LEARNING |
| title_full |
FACIAL RECOGNITION WITH MACHINE LEARNING |
| title_fullStr |
FACIAL RECOGNITION WITH MACHINE LEARNING |
| title_full_unstemmed |
FACIAL RECOGNITION WITH MACHINE LEARNING |
| title_sort |
facial recognition with machine learning |
| url |
https://digilib.itb.ac.id/gdl/view/27419 |
| _version_ |
1821934374652739584 |