Grebenom.zip — Ekipa Sara

: Load the model in evaluation mode and pass the images through. Extract the flattened vector from the global average pooling layer (the layer just before the final classification head).

Deep features are typically the activations from the pre-final layer of a neural network, which act as a condensed numerical representation of the image. : ResNet-18/50 : Good for general tasks and smaller datasets. Ekipa Sara grebenom.zip

: Remove any corrupted files or outliers that do not belong to the "Ekipa Sara grebenom" topic. 2. Pre-processing : Load the model in evaluation mode and

: To improve robustness, apply random rotations, flips, or cropping during the training phase. 3. Feature Extraction Workflow apply random rotations