03312ntm a22005057i 4500 000719652 CZ-PrVSE 20250621144446.0 m d cr n|||||||||| 250621s2024 xr fsbm 000 0 eng d NEZPRACOVANÝ IMPORT ABA006 cze ABA006 ABA006 rda Tatarinov, Vadym ISIS:157992 dis Klasifikace obrázků pomocí metod strojového učení eng Image classification using machine learning methods / Vadym Tatarinov 2024 ?? stran : digital, PDF soubor Vedoucí práce: Lukáš Veverka Bakalářská práce (Bc.)—Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky, 2025 Obsahuje bibliografii Textový (vysokoškolská kvalifikační práce) Rok obhajoby 2025 Recent advancements in deep learning have changed computer vision, evolving from traditional methods like Support Vector Machines (SVM) to Convolutional Neural Networks (CNN) in 2012, and more recently to Vision Transformers (ViT) in 2021. Simultaneously, improvements in computational power and the exponential growth of internet data have further driven this progress. This work uses these developments to build a computer vision model for classifying damaged and undamaged cars. Specifically, the study compares pre-trained convolutional neural networks, such as ResNet and ConvNeXt, to find the best-performing architecture for this task. Key contributions of this work include an analysis of the impact of data quantity and quality on model performance, the balance between computational resources and accuracy, and an exploration of hyperparameter optimization strategies for this application. The model's performance was evaluated using metrics like accuracy, model size, and F1 score, with ConvNeXt achieving a maximum accuracy of 95.4\%, demonstrating its effectiveness in binary classification for this task. The final model from this study could be applied to online platforms or auctions for selling used cars, potentially enhancing ad conversion rates, improving user experience, and reducing fraud associated with selling damaged vehicles. Způsob přístupu: Internet aplikovaná informatika [obor bakal. práce] bakalářské práce fd132403 czenas bachelor's theses eczenas Car damage detection Computer vision Image recognition Image classification Veverka, Lukáš ISIS:118820 ths Kavřík, Dominik ISIS:126085 opn Vysoká škola ekonomická v Praze. Fakulta informatiky a statistiky kn20010709399 dgg https://insis.vse.cz/zp/85049/podrobnosti VŠKP v InSIS https://insis.vse.cz/zp/85049 Hlavní práce https://insis.vse.cz/zp/85049/posudek/vedouci Hodnocení vedoucího https://insis.vse.cz/zp/85049/posudek/oponent/84792 Oponentura https://insis.vse.cz/zp/85049/podrobnosti dc:identifier NEPOSILAT VSKP vse85049 250618 85049