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GUI for Active Learning of Image Detection and Classification
Bureš, Tomáš ; Šůstek, Martin (referee) ; Rozman, Jaroslav (advisor)
With active learning, domain expert doesn't need to annotate the whole dataset, but only those which will allow incremental training of a given model. An example of active learning could be detection and removal of wrong annotations. Another example is detection and expansion of training data which model fails to predict. Description of libraries, frameworks and programs which can be used to integrate with active learning is included in this work. The main part of this work is the design and description of a user interface for active learning. The application allows user to browse dataset, sort annotations and images by multiple criteria and modify annotations generated by active learning model. The application's graphical user interface was implemented with the Vue.js framework and Paper.js library. In conclusion, functionality and future application expansion are discussed.
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Estimation of the Position of the Feet in a Image
Havlíček, Lukáš ; Orság, Filip (referee) ; Goldmann, Tomáš (advisor)
This thesis deals with the design and implementation of solution for estimating the position of the feet in the image, focusing on cases where the feet are covered in the image. The area of anthropometry, neural networks, solution design and implementation and subsequent experiments are described here. The solution uses own convolutional network, implemented using the Keras interface with the creation of own dataset with a focus on covered legs. In the experiments, other points on the body are used to increase accuracy.
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Traffic Analysis Using Machine Learning Approach.
Zelený, O. ; Frýza, T.
This paper provides insight to the YOLOv5 deep learning architecture and its use for vehicle detection and classification in order to improve traffic management in larger cities and busy roads. The paper presents simple system with one fixed camera and Jetson Nano, a computer for embedded and AI application, to detect and classify vehicles.
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Estimation of the Position of the Feet in a Image
Havlíček, Lukáš ; Orság, Filip (referee) ; Goldmann, Tomáš (advisor)
This thesis deals with the design and implementation of solution for estimating the position of the feet in the image, focusing on cases where the feet are covered in the image. The area of anthropometry, neural networks, solution design and implementation and subsequent experiments are described here. The solution uses own convolutional network, implemented using the Keras interface with the creation of own dataset with a focus on covered legs. In the experiments, other points on the body are used to increase accuracy.
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GUI for Active Learning of Image Detection and Classification
Bureš, Tomáš ; Šůstek, Martin (referee) ; Rozman, Jaroslav (advisor)
With active learning, domain expert doesn't need to annotate the whole dataset, but only those which will allow incremental training of a given model. An example of active learning could be detection and removal of wrong annotations. Another example is detection and expansion of training data which model fails to predict. Description of libraries, frameworks and programs which can be used to integrate with active learning is included in this work. The main part of this work is the design and description of a user interface for active learning. The application allows user to browse dataset, sort annotations and images by multiple criteria and modify annotations generated by active learning model. The application's graphical user interface was implemented with the Vue.js framework and Paper.js library. In conclusion, functionality and future application expansion are discussed.
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