Which are the segmentation algorithms proposed during 2018-2019 in CVPR that have CNN architecture?’ Answering this question involves identifying and analyzing the deep learning architecture diagrams ...

As the title suggests, this paper studies various different deep convolutional neural network architectures and various techniques to use these CNNs for CADe (Computer Aided Detection) tasks. With the ...

Deep learning began to emerge in the 1990s, and with the development and updating of networks, higher requirements were placed on data set analysis techniques. Firstly, it elaborates on the ...

In addition to pure deep neural networks (DNNs), sometimes people use hybrid vision models, which combine deep learning with classical machine learning algorithms that perform specific sub-tasks.

Deep Learning Algorithms. For brain MR image analysis, we used a convolutional neural network (CNN) implemented using the Python programming language. TensorFlow 2.4, Keras, and scikit-learn 0.23.2 ...

RetinaNet is a one-stage high-accuracy deep learning algorithm that uses a Feature Pyramid Network (FPN) chelation on CNN as its backbone network. It attaches two sub-networks respectively for anchor ...