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Found 6 papers, 2 papers with code
Cascade Residual Learning: A Two-stage Convolutional Neural Network for Stereo Matching
As opposed to directly learning the disparity at the second stage, we show that residual learning provides more effective refinement.
Shepard Convolutional Neural Networks
In this paper, we draw on Shepard interpolation and design Shepard Convolutional Neural Networks (ShCNN) which efficiently realizes end-to-end trainable TVI operators in the network.
On Vectorization of Deep Convolutional Neural Networks for Vision Tasks
We recently have witnessed many ground-breaking results in machine learning and computer vision, generated by using deep convolutional neural networks (CNN).
Deep Convolutional Neural Network for Image Deconvolution
Many fundamental image-related problems involve deconvolution operators.
Ranked #1 on
Image Compression
on FER2013
An Unsupervised Feature Learning Approach to Improve Automatic Incident Detection
Sophisticated automatic incident detection (AID) technology plays a key role in contemporary transportation systems.
Exploring The Contribution of Unlabeled Data in Financial Sentiment Analysis
We argue that if the bias-variance trade-off is to be better balanced by a more effective feature selection method unlabeled data is very likely to boost the classification performance.
