A deep learning architecture employs a Convolutional Neural…
A deep learning architecture employs a Convolutional Neural Network (CNN) backbone and a Feature Pyramid Network (FPN) to extract multiscale features containing spatial information. A Region Proposal Network (RPN) generates candidate object regions, which are processed through ROI Align. The architecture includes separate prediction heads responsible for object classification, bounding-box regression, and pixel-level segmentation. The segmentation head utilizes transposed convolutions to convert Region of Interest features into a pixel-level object mask. During training, pixel-wise binary cross-entropy loss evaluates the predicted masks against ground-truth masks, enabling accurate instance-level segmentation across various object categories.Which of the following deep learning architectures is represented by the description?
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