In 1989, Yann LeCun helped show that neural networks could read handwritten ZIP codes ...

In 1989, a computer scientist tackled the messy challenge of reading handwritten zip codes for the US Post Office. This ...
IEEE

diffGrad: An Optimization Method for Convolutional Neural Networks

Abstract: Stochastic gradient descent (SGD) is one of the core techniques behind the success of deep neural networks. The gradient provides information on the direction in which a function has the ...
GitHub

alelab-upenn/graph-neural-networks

F. Gama, A. G. Marques, G. Leus, and A. Ribeiro, "Convolutional Neural Network Architectures for Signals Supported on Graphs," IEEE Trans. Signal Process., vol. 67 ...
Frontiers

Fully convolutional neural networks applied to large-scale marine morphology mapping

In this study we applied for the first time Fully Convolutional Neural Networks (FCNNs) to a marine bathymetric dataset to derive morphological classes over the entire Irish continental shelf. FCNNs ...
Investopedia

Neural Networks in Finance: Fundamentals, Varieties, and Applications

James Chen, CMT is an expert trader, investment adviser, and global market strategist. Andy Smith is a Certified Financial Planner (CFP®), licensed realtor and educator with over 35 years of diverse ...
PNAS

NeuronMotif: Deciphering cis-regulatory codes by layer-wise demixing of deep neural networks

Cis-regulatory sequences regulate the expression of nearby genes. Recently, remarkable advances in our ability to predict the function of cis-regulatory sequences have been achieved by using ...
GitHub

Super-Resolution imaging with Convolutional Neural Network

This is an open source project from original of this: SRCNN_Cpp is a C++ Implementation of Image Super-Resolution using SRCNN which is proposed by Chao Dong in 2014. If you want to find the details of ...
IEEE

Reduced Biquaternion Convolutional Neural Network for Color Image Processing

Abstract: Reduced biquaternion is a four dimensional hyper–complex number which is commutative algebra and an extension of complex. Due to this property, the corresponding fast algorithm is designed ...
Frontiers

Geometric Convolutional Neural Network for Analyzing Surface-Based Neuroimaging Data

In machine learning, one of the most popular deep learning methods is the convolutional neural network (CNN), which utilizes shared local filters and hierarchical information processing analogous to ...