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ImageNet

Known as: ImageNet Large Scale Visual Recognition Challenge, ImageNet competition 
The ImageNet project is a large visual database designed for use in visual object recognition software research. As of 2016, over ten million URLs of… 
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Related topics

Related topics

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Computer visionDatabaseDeep learningDeepDream

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2019
2019
Enhanced Transfer Learning with ImageNet Trained Classification Layer
Parameter fine tuning is a transfer learning approach whereby learned parameters from pre-trained source network are transferred… 
2018
2018
Prototype-based Neural Network Layers: Incorporating Vector Quantization
Neural networks currently dominate the machine learning community and they do so for good reasons. Their accuracy on complex… 
Highly Cited
2017
Highly Cited
2017
Learning and Transferring Convolutional Neural Network Knowledge to Ocean Front Recognition
In this letter, we investigated how to apply a deep learning method, in particular convolutional neural networks (CNNs), to an… 
2017
2017
Action unit selective feature maps in deep networks for facial expression recognition
Facial expression recognizers based on handcrafted features have achieved satisfactory performance on many databases. Recently… 
2016
2016
Bottom-Up Top-Down Cues for Weakly-Supervised Semantic Segmentation
We consider the task of learning a classifier for semantic segmentation using weak supervision in the form of image labels… 
Highly Cited
2016
Highly Cited
2016
Deep Learning for Algorithm Portfolios
It is well established that in many scenarios there is no single solver that will provide optimal performance across a wide… 
2015
2015
Distributed Neural Networks for Internet of Things: The Big-Little Approach
Nowadays deep neural networks are widely used to accurately classify input data. An interesting application area is the Internet… 
Highly Cited
2014
Highly Cited
2014
Logarithmic Time Online Multiclass prediction
We study the problem of multiclass classification with an extremely large number of classes (k), with the goal of obtaining train… 
2014
2014
Learning From Weakly Supervised Data by The Expectation Loss SVM (e-SVM) algorithm
In many situations we have some measurement of confidence on "positiveness" for a binary label. The "positiveness" is a… 
Review
2014
Review
2014
Knowledge Bases in the Age of Big Data Analytics
This tutorial gives an overview on state-of-the-art methods for the automatic construction of large knowledge bases and… 
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