Squeeze-and-Excitation Networks
The central building block of convolutional neural networks (CNNs) is the convolution operator, which enables networks to construct informative features by fusing both spatial a...
Publications
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1,458 publications
Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments
The problem of identifying differentially expressed genes in designed microarray experiments is considered. Lonnstedt and Speed (2002) derived an expression for the posterior od...
Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring
Although cancer classification has improved over the past 30 years, there has been no general approach for identifying new cancer classes (class discovery) or for assigning tumo...
Structure, function and diversity of the healthy human microbiome
Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin and vagina. Much of this...
Semiconductor Clusters, Nanocrystals, and Quantum Dots
Current research into semiconductor clusters is focused on the properties of quantum dots—fragments of semiconductor consisting of hundreds to many thousands of atoms—with the b...
A survey on Image Data Augmentation for Deep Learning
Abstract Deep convolutional neural networks have performed remarkably well on many Computer Vision tasks. However, these networks are heavily reliant on big data to avoid overfi...
Large-Area Synthesis of High-Quality and Uniform Graphene Films on Copper Foils
Growing Graphene The highest quality graphene samples, single-atom-thick layers of carbon, are suspended flakes exfoliated from graphite, but these samples are very small in siz...
Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications
The purpose of this study was to classify breast carcinomas based on variations in gene expression patterns derived from cDNA microarrays and to correlate tumor characteristics ...
Non-local Neural Networks
Both convolutional and recurrent operations are building blocks that process one local neighborhood at a time. In this paper, we present non-local operations as a generic family...