Abstract: Image classification plays an important role in remote sensing. Earth observation (EO) has inevitably arrived in the big data era, but the high requirement on computation power has already ...

This tutorial was designed for easily diving into TensorFlow, through examples. For readability, it includes both notebooks and source codes with explanation, for ...

本章内容主要基于 Pytorch 官方入门教程编写，使用 C# 代码代替 Python，主要内容包括处理数据、创建模型、优化模型参数、保存模型、加载模型，读者通过本章内容开始了解 TorchSharp 框架的使用方法。 首先添加以下代码，查找最适合当前设备的工作方式，主要是 ...

We present a novel software feature for the BrainScaleS-2 accelerated neuromorphic platform that facilitates the partitioned emulation of large-scale spiking neural networks. This approach is well ...

The MNIST dataset is a set of 70,000 human-labeled 28 x 28 greyscale images of individual handwritten digits. It is a subset of a larger dataset available from NIST - The National Institute of ...

Quantum Convolutional Neural Network (QCNN) has achieved significant success in solving various complex problems, such as quantum many-body physics and image recognition. In comparison to the ...

The self-attention-based transformer model was first introduced by Vaswani et al. in their paper Attention Is All You Need in 2017 and has been widely used in natural language processing. A ...

来源于谷歌的TensorFlow是目前Python编程领域最热门的深度学习框架。Google不仅是大数据和云计算的领导者，在机器学习和深度学习上也有很好的实践和积累，在2015年年底开源了内部使用的深度学习框架TensorFlow。 与Caffe、Theano、Torch、MXNet等框架相比，TensorFlow在 ...

We introduce Intensive Principal Component Analysis (InPCA), a widely applicable manifold-learning method to visualize general probabilistic models and data. Using replicas to tune dimensionality in ...