Abstract: The convolutional neural networks (CNNs) have recently demonstrated to be a powerful tool for object detection. However, with the complex scenes in remote sensing images, feature extraction ...

For that purpose, we proposed a method for automatic object detection based on a convolutional neural network. A novel two-stage approach for network training is implemented and verified in the tasks ...

Considering that traditional image processing approaches rely heavily on feature extraction operators and are not robust enough, we conduct a detailed study of convolutional neural networks. In object ...

All convolution layers are used to extract the input image feature. The model also has 2 max pooling layers used to reduce the dimensions of the output volume. The last two layers are the flattened ...

With the development of artificial intelligence, the algorithms of convolutional neural network ... Image classification is the popular application of CNN algorithms. Recently, scientists tried to ...

The increasing availability of powerful light microscopes capable of collecting terabytes of high-resolution 2D and 3D videos in ... we developed a convolutional neural network for particle ...

Convolutional neural networks (CNNs) are a class of deep neural networks commonly used in computer vision tasks such as image and video recognition, object detection and image segmentation.