Can we use feature maps to detect and mitigate the effects of data bias?

Our method does not require fine-tuning the network weights and halves the data transfer volumes to the main memory by compressing feature maps, which are ... a feature map of 13*13 will be obtained for images with the size of 416*416 ... Weld defect map recognition based on improved Faster R-CNN [J]. China ... map tensor, both the current partial feature-map tensor and the selected index ... The transmission probabilities of feature maps for the case of CNN. Feature maps are a core component of convolutional neural networks as they capture essential features from the input image to aid the network in decision-making ... Jun 15, 2024 ... using single-scale feature maps. In CNN early stage, the feature map contains low-level features with accurate localization information ... In this paper, we propose strategies to enable CNN inference accelerators to have an adjustable feature map compression ratio, making them tunable regarding ... Jan 31, 2019 ... ... feature map sizes for CNN configuration. Six configurations are ... Classification, Functional MRI, Deep learning, CNN, Feature map. May 24, 2023 ... During the forward pass of a CNN, the input image is convolved with one or more filters to produce multiple feature maps. Each feature map ... Jul 7, 2024 ... ... Convolutional Neural Network (CNN) archi ... A CNN Architecture Tailored For Quantum Feature Map-Based Radar Sounder Signal Segmentation. Sep 17, 2018 ... These so-called feature maps are the outputs of the convolutions that take place using the input color channels and the convolutional filters.