What are some promising future research directions in the field of feature map analysis and interpretation in CNNs?

Jul 7, 2024 ... ... Convolutional Neural Network (CNN) archi ... A CNN Architecture Tailored For Quantum Feature Map-Based Radar Sounder Signal Segmentation. In the traditional person re-identification model, the CNN network is usually used for feature extraction. When converting the feature map into a feature ... Jul 11, 2021 ... Model compactness As a result of the use of different filter sizes with feature concatenation and skip connections at every stage, feature maps ... Jan 1, 2023 ... keywords = "CNN, Feature map Augmentation, Global Features, Scale-Invariant, Vision System, Convolutional Neural Network, Feature Map ... Feb 11, 2021 ... We propose to develop deep learning models to recognize EGFR status by using radiomics features extracted from non-invasive CT images. Jan 26, 2023 ... Let's start visualizing the feature maps in Convolutional Neural Networks (CNN). We will see what the Convolutional filters are looking for ... Nov 21, 2020 ... Steps to generate feature maps:- · for layer_name, feature_map in zip(layer_names, feature_maps): · if len(feature_map.shape) == 4 k = ... Nov 21, 2022 ... In Convolutional Neural Networks we extract and create abstractified “feature maps” of our given image. My thought was this: We extract things like lines ... The feature maps generated will be sent to the next layer in the deep CNN. The data volume is much higher since the input is now an image instead of a ... ... features within the receptive field. The feature maps are obtained by sliding the PQCs over the input in a similar way as CNN. We also give a training ...