What are some current research trends related to understanding and utilizing feature maps in CNNs?

Mar 19, 2022 ... What is a Convolutional Neural Network (CNN)? · Convolutional layer: abstracts the input image as a feature map via the use of filters and ... 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 ... Jun 13, 2022 ... Can we deduce what number of Conv2D layers that are sufficient ? deep-learning · convolutional-neural-network · feature-extraction · feature-map. Oct 22, 2017 ... Specifically, we develop a convolutional neural network (CNN) to classify the feature map sets extracted from the tertiary protein structures. In this next section, you're going to take a peek inside your network to see what sorts of features your models are learning at different layers. May 26, 2023 ... We propose augmenting intermediate feature maps of CNNs. Specifically, we pass them through a novel Augmentation Layer to prevent models from overfitting. Apr 23, 2015 ... ... CNN) use simple multi-layer perceptrons. This paper demonstrates that carefully designing deep networks for object classification is just as ... Jan 29, 2017 ... Instead of using max-pooling layers to reduce the size of the feature maps, we use convolution layers with increased strides. Mar 25, 2024 ... ... features increases. How a CNN model works. After passing through the last convolutional layer, the values within each feature map ... Feature Map Transfer: Vertical Federated Learning for CNN Models. Tianchi Sha, Xiao Yu, Zhiwei Shi, Yuan Xue, Shouxin Wang, Sikang Hu*.