Can we design custom loss functions that encourage the learning of specific types of features?

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 = ... Jan 1, 2023 ... keywords = "CNN, Feature map Augmentation, Global Features, Scale-Invariant, Vision System, Convolutional Neural Network, Feature Map ... (CNN + LSTM) (CNN + Reinforcement Learning). Page 4. Convolutional ... • Line Buffer Size << Feature Map Size. Feature Map. 3*3 Kernel x. Layer i. ✔️. This multi-feature map represents a sample composed of two residues on a trimer protein. Secondly, we construct a CNN-GRU deep learning framework to predict the ... ... feature map but does not change the number of feature maps. The window size, in Pool.1, is w1 × dh. In Conv.2, each kind of input feature map is calculated ... Oct 22, 2017 ... Specifically, we develop a convolutional neural network (CNN) to classify the feature map sets extracted from the tertiary protein structures. Jun 27, 2021 ... Feature maps in CNN. Now, let's go over a few important terms that ... feature map containing the most dominant features of the previous feature ... ... map during 20–60 s interval of N-back tasks. Our results indicate that ... CNN model with ΔHbO maps and temporal feature maps above. Finally, we used ... In this paper, we design a light CNN architecture that addresses these challenges. Specifically, we implemented Max-feature-map (MFM) into each convolutional ... Pooling: In a CNN's pooling layers, feature maps are divided into rectangular sub-regions, and the features in each rectangle are independently down-sampled ...