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  3. Computational Imaging (LTAT.02.025)
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Computational Imaging 2023/24 spring

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HW3. Image Classification, Data Augmentation, Pre-Trained Models (14th April, 23.59)

EX1 (5p) : Your task is Image Classification Task from the classifier code given below and plot model loss and model accuracy. Complete the cells. You need to upload your plots and code.

https://colab.research.google.com/drive/1T1SBiL5iSjH4homzpIpGIQwYYgeAeine#scrollTo=57CcilYSG0zv

EX2 (5p) : This task is to build a CNN from the scratch. The CNN has different modules. In this task you need to build a Zero-padding only. https://colab.research.google.com/drive/1bHRhl9Pip0h8Xjrt_hxmOI4wAbqSSHjP#scrollTo=y4viGvO40VIA

EX3 (5p) : This exercise is to build a classifier using the Cats v Dogs dataset of 25k images! sed You have to train a convolutional neural network for the classification.

You will see the CNN overfit very quickly, despite great results with the training set.

Complete the notebook and upload your results.

https://colab.research.google.com/drive/1SsdYGrvglje8bhPc0GuFcBSJs9Jt0mor#scrollTo=6f375c5d

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  • University of Tartu
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