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Found 7 papers, 2 papers with code
Lesion Conditional Image Generation for Improved Segmentation of Intracranial Hemorrhage from CT Images
A lesion conditional image (segmented mask) is an input to both the generator and the discriminator of the LcGAN during training.
DeepSat V2: Feature Augmented Convolutional Neural Nets for Satellite Image Classification
Satellite image classification is a challenging problem that lies at the crossroads of remote sensing, computer vision, and machine learning.
Ranked #1 on
Satellite Image Classification
on SAT-4
Pixel-level Reconstruction and Classification for Noisy Handwritten Bangla Characters
Classification techniques for images of handwritten characters are susceptible to noise.
Ranked #1 on
Document Image Classification
on n-MNIST
Core Sampling Framework for Pixel Classification
The intermediate map responses of a Convolutional Neural Network (CNN) contain information about an image that can be used to extract contextual knowledge about it.
A Theoretical Analysis of Deep Neural Networks for Texture Classification
To this end, we first derive the size of the feature space for some standard textural features extracted from the input dataset and then use the theory of Vapnik-Chervonenkis dimension to show that hand-crafted feature extraction creates low-dimensional representations which help in reducing the overall excess error rate.
Learning Sparse Feature Representations using Probabilistic Quadtrees and Deep Belief Nets
Learning sparse feature representations is a useful instrument for solving an unsupervised learning problem.
DeepSat - A Learning framework for Satellite Imagery
Satellite image classification is a challenging problem that lies at the crossroads of remote sensing, computer vision, and machine learning.
Ranked #2 on
Satellite Image Classification
on SAT-6
