Analysis of Image Classification Deep Learning Algorithm

dc.contributor.authorKanungo, Shivam
dc.date.accessioned2023-06-02T20:13:18Z
dc.date.available2023-06-02T20:13:18Z
dc.date.issued2023
dc.description.abstractThis study explores the use of TensorFlow 2 and Python for image classification problems. Image categorization is an important area in computer vision, with several real-world applications such as object identification/recognition, medical imaging, and autonomous driving. This work studies TensorFlow 2 and its image categorization capabilities. We also demonstrate how to construct an image classification model using Python and TensorFlow 2. This analysis of image classification neural network problems with the use of Convolutional Neural Network (CNN) on the German and the Chinese traffic sign datasets is an engineering task. Ultimately, this work provides step-by-step guidance for creating an image classification model using TensorFlow 2 and Python, while also showcasing its potential to tackle image classification issues across various domains.en_US
dc.identifier.urihttps://hdl.handle.net/10365/33210
dc.publisherNorth Dakota State Universityen_US
dc.rightsNDSU policy 190.6.2en_US
dc.rights.urihttps://www.ndsu.edu/fileadmin/policy/190.pdfen_US
dc.titleAnalysis of Image Classification Deep Learning Algorithmen_US
dc.typeMaster's paperen_US
ndsu.advisorLudwig, Simone
ndsu.collegeEngineeringen_US
ndsu.degreeMaster of Science (MS)en_US
ndsu.departmentComputer Scienceen_US

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