[Places365] Data for "Exploring specialization and sensitivity of convolutional neural networks in the context of simultaneous image augmentations"

This repository contains data collected under the following study:P.Kharyuk, S.Matveev, I.Oseledets. Exploring specialization and sensitivity of convolutional neural networks in the context of simultaneous image augmentations, arXiv:2503.03283. Corresponding source code repository: https://github.com/kharyuk/activation_sa ILSVRC-based part: 10.5281/zenodo.18097911 0_models.7z: copy of the CNN models used in the research (reference: http://places2.csail.mit.edu) 1_sensitivity_values.7z: sensitivity values (Sobol indices, Shapley values) computed for the first experimental series. In addition, logs and npz-files containing the sampled parameters were packed. To be used within the jupyter notebooks, all .hdf5 files should be placed into the 'results' directory of the source code repository. 2_guided_masking_predictions.7z: these files include the top-5 class predictions and corresponding classifying layer's outputs computed for the second experimental series. Every .hdf5 file should be placed into the 'results' directory of the source code repository. Logs and pkl files with sampling parameters are also included in the archive. The unpacking procedure for archives 1-2 is automated by the bash script located in tools/unpack_results.sh of the GitHub repository.