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Materials of football shoes
Ponížil, Ondřej ; Doležal, Pavel (referee) ; Molliková, Eva (advisor)
This thesis is about materials of football boots and possibilities of their technological process. The thesis is divided into three main parts. The introduction part contains the basic facts about football and there is also a description of historical development of the football boots which includes advantages and disadvantages of the structure at that time. The second part presents permeable, flexible and durable materials which can be used to produce the upper part of the boots. In this part there are described attributes of the most common technological process which produces synthetic leathers. The final part is about polyamides and thermoplastics elastomers from which the football soles are made.
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Automatic Image Analysis for Production Quality Control of Textile
Sýkorová, Tereza ; Dobeš, Petr (referee) ; Zemčík, Pavel (advisor)
This work deals with the classification of defects that occur in the production of nonwovens. The defect classification task is part of a system for automatic production quality control. The goal is to implement a method that will classify problematic defect classes with sufficient accuracy. That was achieved using convolutional neural networks (CNN). The best results were achieved by the EfficientNet network, which had an accuracy of 81% when evaluated by cross-validation on an available dataset. Within the work, a number of experiments are performed, which are focused on the modification of input data. The influence of the shape and composition of the input images on the final classification is examined. A CNN model was also implemented, which uses additional information for classification in addition to the image.
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Automatic Image Analysis for Production Quality Control of Textile
Sýkorová, Tereza ; Dobeš, Petr (referee) ; Zemčík, Pavel (advisor)
This work deals with the classification of defects that occur in the production of nonwovens. The defect classification task is part of a system for automatic production quality control. The goal is to implement a method that will classify problematic defect classes with sufficient accuracy. That was achieved using convolutional neural networks (CNN). The best results were achieved by the EfficientNet network, which had an accuracy of 81% when evaluated by cross-validation on an available dataset. Within the work, a number of experiments are performed, which are focused on the modification of input data. The influence of the shape and composition of the input images on the final classification is examined. A CNN model was also implemented, which uses additional information for classification in addition to the image.
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Materials of football shoes
Ponížil, Ondřej ; Doležal, Pavel (referee) ; Molliková, Eva (advisor)
This thesis is about materials of football boots and possibilities of their technological process. The thesis is divided into three main parts. The introduction part contains the basic facts about football and there is also a description of historical development of the football boots which includes advantages and disadvantages of the structure at that time. The second part presents permeable, flexible and durable materials which can be used to produce the upper part of the boots. In this part there are described attributes of the most common technological process which produces synthetic leathers. The final part is about polyamides and thermoplastics elastomers from which the football soles are made.
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