With the advancement of computer technology, the power of the artificial network was also increased. Thesis, describe the process of making, training and the result of using neural networks. Main goal was to classify individual objects covered by a Go pro camera. The latter is attached to the top of the self-driving boat. By using segmentation, the boat can "detect" objects in the surrounding area. The process of determining the classifications of individual images is called semantic segmentation.
Due to the lack of annotated sea image bases, it was also necessary to produce the training images. The middle section described a structure of a convolutional neural network. This one consisted of two parts. The first part, called the encoder that is used to identify objects. The second part is called a decoder, which determines the spatial location of the encoder data. The last sections show the results in the measurements obtained from neural network. The obtained results were used to determine, if the camera could be used as one of the sensors for detecting surrounding area. It was also necessary to present how different factors such as location, image size in image quality affect the results.
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