What are some techniques for manipulating feature maps (e.g., gradient-based methods)?

Jul 13, 2021 ... ... feature map. However, in CNN, pooling is applied to feature maps that result from each filter. Flattening. You can think of CNN as a sequence ... Proposed method converts ... Feature maps are fundamental outputs generated by the layers within a Convolutional Neural Network (CNN), particularly the convolutional layers. Jan 29, 2017 ... Instead of using max-pooling layers to reduce the size of the feature maps, we use convolution layers with increased strides. In this paper, we propose strategies to enable CNN inference accelerators to have an adjustable feature map compression ratio, making them tunable regarding ... Mar 27, 2025 ... Each convolutional layer applies a set of filters to detect features from the input images. A CNN layer gives feature maps as its output. We will explain what feature and feature map are later on. ... This creates the spatial invariance of ConvNet. Figure 7. Visualizing CNN feature maps and ... The resulting output O O O is called feature map or activation map. Remark ... CNN and Faster R-CNN. Face verification and recognition. Types of models ... CNN Feature Maps and Object Saliency Maps. Wataru Shimoda and Keiji Yanai ... map can be obtained by up-sampling saliency maps of the intermediate ... Feature Map Transfer: Vertical Federated Learning for CNN Models. Tianchi Sha, Xiao Yu, Zhiwei Shi, Yuan Xue, Shouxin Wang, Sikang Hu*.