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Implementation of the information system
Chovaneček, Přemysl ; Dyk, Tomáš (referee) ; Novák, Lukáš (advisor)
The thesis describes the design and implementation of an information system for a small business company. The thesis includes strategic analyzes of the company and an assessment of the current situation associated with the Covid-19 pandemic. Subsequently, the thesis describes the process of specification and analysis of the requirements of the client, the design and implementation of the system corresponding to the proposals. Finally, the thesis provides the evaluation and expected benefits of the information system.
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Graffiti Tags Detection Mobile Application
Chovaneček, Přemysl ; Teuer, Lukáš (referee) ; Špaňhel, Jakub (advisor)
Thesis focuses on the object recognition of images, using the principles of artificial intelligence. It solves the signature detection of authors in the field of art called graffiti. It concerns about basic problematic of this field, it also points to the use of computer vision followed by practical application on mobile devices, specifically on the Android platform. The selected neural network models was the ssdMobileNet_v2 . The trained model achieves mAP accuracy of 73.5% meanwhile the IoU was set to 0.6. After the quantization process, the accuracy was reduced to 68.5%. The mobile application provides real-time detection and several other necessary functions for localization and data collection.
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Implementation of the information system
Chovaneček, Přemysl ; Dyk, Tomáš (referee) ; Novák, Lukáš (advisor)
The thesis describes the design and implementation of an information system for a small business company. The thesis includes strategic analyzes of the company and an assessment of the current situation associated with the Covid-19 pandemic. Subsequently, the thesis describes the process of specification and analysis of the requirements of the client, the design and implementation of the system corresponding to the proposals. Finally, the thesis provides the evaluation and expected benefits of the information system.
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|
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Graffiti Tags Detection Mobile Application
Chovaneček, Přemysl ; Teuer, Lukáš (referee) ; Špaňhel, Jakub (advisor)
Thesis focuses on the object recognition of images, using the principles of artificial intelligence. It solves the signature detection of authors in the field of art called graffiti. It concerns about basic problematic of this field, it also points to the use of computer vision followed by practical application on mobile devices, specifically on the Android platform. The selected neural network models was the ssdMobileNet_v2 . The trained model achieves mAP accuracy of 73.5% meanwhile the IoU was set to 0.6. After the quantization process, the accuracy was reduced to 68.5%. The mobile application provides real-time detection and several other necessary functions for localization and data collection.
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