Mid-levelMultiple choiceIs it a good idea to use CNN to classify 1D signals?ANo, CNNs cannot handle temporal dependencies.BNo, CNNs are not suitable for any 1D data.CYes, CNNs can find repeating patterns in 1D signals.DYes, because CNNs are the most popular for time-series data.Check answer
Mid-levelMultiple choiceWhat is the purpose of data augmentation in computer vision?ATo reduce the size of the training datasetBTo artificially increase the size and diversity of a training datasetCTo decrease the model's generalization abilityDTo ensure the model memorizes specific examples in the training dataCheck answer
JuniorMultiple choiceWhich of the following is NOT a common data augmentation technique in computer vision?AHorizontal FlippingBRandom RotationCVertical FlippingDData PruningCheck answer
Mid-levelMultiple choiceWhat is the benefit of using Gaussian noise as a data augmentation technique?AIt simulates noisy environments and enhances the model's noise toleranceBIt decreases the diversity of the training datasetCIt reduces the model's noise toleranceDIt ensures the model focuses on specific examplesCheck answer
JuniorMultiple choiceWhat is a Convolutional Neural Network (CNN)?AA network designed to work with sequential data like text or time series.BA deep learning model mainly used for image recognition, computer vision, and pattern detection.CA type of neural network used for text processing.DA method to prevent overfitting in neural networks.Check answer
