Can feature maps be used for fine-grained image recognition?

We present a method for boosting the performance of the Convolutional Neural Network (CNN) by reducing the covariance between the feature maps of the ... Jun 15, 2024 ... using single-scale feature maps. In CNN early stage, the feature map contains low-level features with accurate localization information ... Proposed method converts ... Jul 28, 2023 ... In CNNs, feature maps are the output produced after applying the convolution operation with different filters. Each feature map corresponds to a ... Feb 12, 2021 ... We propose to develop deep learning models to recognize EGFR status by using radiomics features extracted from non-invasive CT images. map tensor, both the current partial feature-map tensor and the selected index ... The transmission probabilities of feature maps for the case of CNN. neural network or say (S-CNN), pretrained CNN feature extractor, and hierarchical extreme learning machine ... In the top-down pathway, a subsequent feature map ... Jul 7, 2024 ... ... Convolutional Neural Network (CNN) archi ... A CNN Architecture Tailored For Quantum Feature Map-Based Radar Sounder Signal Segmentation. Feature Map Transfer: Vertical Federated Learning for CNN Models. Tianchi Sha, Xiao Yu, Zhiwei Shi, Yuan Xue, Shouxin Wang, Sikang Hu*. 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 ...