Are there other activation functions used after convolution, and how do they affect the feature maps?

map tensor, both the current partial feature-map tensor and the selected index ... The transmission probabilities of feature maps for the case of CNN. 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 = ... This article presents a hybrid quantum-classical framework by incorporating quantum feature maps regulated classical Convolutional Neural Network (CNN) ... We present a method for boosting the performance of the Convolutional Neural Network (CNN) by reducing the covariance between the feature maps of the ... Aug 18, 2018 ... After finishing the previous two steps, we're supposed to have a pooled feature map by now. As the name of this step implies, ... Nov 14, 2022 ... The network has three convolutional layers, as follows: Layer 1: Number of feature maps =8 Size of a feature map =220×220 Layer 2: Number of ... The implemented techniques are: feature map visualization, backward optimization and layer-wise relevance propagation. Since our model reaches a good accuracy ... Oct 12, 2021 ... In this paper, we propose an efficient hardware accelerator with an interlayer feature compression technique to significantly reduce the required on-chip ... Oct 28, 2022 ... map of layer k, ak is the activation map of layer k. In this study, we visualize the feature maps fk. 258. 2.5.2 Backward optimisation (BO). 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 ...