What are the challenges in using feature maps for small object detection?

In this paper, we propose strategies to enable CNN inference accelerators to have an adjustable feature map compression ratio, making them tunable regarding ... If you don't have access, please check back again shortly as we launch this new feature. ... CNN StoreNewslettersTranscriptsLicense FootageCNN NewsourceSitemap. © ... 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 ... A local feature CNN extracts the coarse-level feature maps F ~ A and F ~ ... feature map. Coarse matches will be refined within this local window to a sub ... May 17, 2015 ... In a Convolutional Neural Network (CNN), a feature map is the output of one filter applied to the previous layer. The concept of a feature map ... 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 ... Experimental results show that our proposed ACFM approach can improve a CNN's camera model identification robust- ness to resampling and JPEG compression. 2. Apr 2, 2025 ... Pooling layer is used in CNNs to reduce the spatial dimensions (width and height) of the input feature maps while retaining the most important information. ... CNN, and it is where the majority of computation occurs. It requires a few components, which are input data, a filter and a feature map. Let's assume that ... map tensor, both the current partial feature-map tensor and the selected index ... The transmission probabilities of feature maps for the case of CNN.