The field of dynamical systems is being transformed by the mathematical tools and
algorithms emerging from modern computing and data science. First-principles derivations …

In real-world recognition/classification tasks, limited by various objective factors, it is usually
difficult to collect training samples to exhaust all classes when training a recognizer or …

信号采样是联系模拟信源和数字信息的桥梁. 人们对信息的巨量需求造成了信号采样,
传输和存储的巨大压力. 如何缓解这种压力又能有效提取承载在信号中的有用信息是信号与信息 …

压缩感知是建立在矩阵分析, 统计概率论, 拓扑几何, 优化与运筹学, 泛函分析等基础上的一种
全新的信息获取与处理的理论框架. 它基于信号的可压缩性, 通过低维空间, 低分辨率, 欠Nyquist …

The development of artificial intelligence is typically focused on computer algorithms and
integrated circuits. Recently, all-optical diffractive deep neural networks have been created …

People``understand''the world via vision, hearing, tactile, and also the past experience.
Human experience can be learned through normal learning (we call it explicit knowledge) …

In the image fusion field, the design of deep learning-based fusion methods is far from
routine. It is invariably fusion-task specific and requires a careful consideration. The most …

Semi-supervised learning is the branch of machine learning concerned with using labelled
as well as unlabelled data to perform certain learning tasks. Conceptually situated between …

In this article, we propose a novel method for infrared and visible image fusion where we
develop nest connection-based network and spatial/channel attention models. The nest …

Recently, over-parameterized deep networks, with increasingly more network parameters
than training samples, have dominated the performances of modern machine learning …