Based on the numerical manifold method principle, we developed a mathematical framework of a neural network manifold: Deep Manifold and discovered that neural networks: 1) is numerical computation combining forward and inverse; 2) have near infinite degrees of freedom; 3) exponential learning capacity...
The neurons we studied are linear neurons that are capable of learning linear functions. They are not suited for learning representations that are nonlinear in nature. Practically, almost all the inputs that neural networks are fed with are nonlinear in nature. In the next section, we are going...
Michael Nielson in his online book Neural Networks and Deep Learning describes this quite well: Somewhat confusingly, and for historical reasons, such multiple layer networks are sometimes called multilayer perceptrons or MLPs , despite being made up of sigmoid neurons, not perceptrons. We are going...
Anatomy Of High-Performance Deep Learning Convolutions On SIMD Architectures Convolution layers are prevalent in many classes of deep neural networks, including Convolutional Neural Networks (CNNs) which provide state-of-the-art res... E Georganas,S Avancha,K Banerjee,... 被引量: 4发表: 2018...
In Proceeding of IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks 2014, pages 1–6. IEEE Kaspersky (2017) Chasing lazarus: a hunt for the infamous hackers to prevent large bank robberies. https://www.kaspersky.com/about/press-releases/2017_chasing-lazarus-a-...
Nevertheless, the training of deep neural networks typically requires a significantly large amount of annotated data, which is not always available. A proven approach to alleviate the scarcity of annotated data is transfer learning. However, in practice, the use of this technique typically relies on...
We design a framework based on Mask Region-based Convolutional Neural Network to automatically detect and separately extract anatomical components of mosquitoes-thorax, wings, abdomen and legs from images. Our training dataset consisted of 1500 smartphon
EM Meyers,XL Qi,C Constantinidis - 《Proceedings of the National Academy of Sciences of the United States of America》 被引量: 100发表: 2012年 The Anatomy of Memory. Reports that an inquiry into the roots of human amnesia has shown how deep structures in the brain may interact with perpe...
[2] Also, as you will see in the Auto-differentiation part, it’s not clear how you would calculate the derivatives of words. They’re not even continuous! [3] This is the (in)famous backpropagation algorithm and is central to learning in Multilayered neural networks. ...
Furthermore, we have shown that neural networks can be combined with augmented reality as a rising field, and the great potential of augmented reality and neural networks to be employed for medical learning and education systems. 展开 关键词: Neural network Augmented reality 3D reconstruction ...