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Deep Dive into Semi-Supervised ELBO for Improving Classification Performance
Experiments on a diverse datasets verify that our method can be used to improve the classification performance of existing VAE based semi-supervised models.
A Novel Disaster Image Dataset and Characteristics Analysis using Attention Model
In this research, we have carefully accumulated a relatively challenging dataset that contains images collected from various sources for three different disasters: fire, water and land.
Attention Toward Neighbors: A Context Aware Framework for High Resolution Image Segmentation
High-resolution image segmentation remains challenging and error-prone due to the enormous size of intermediate feature maps.
Deep-learning coupled with novel classification method to classify the urban environment of the developing world
Image encompassing 70% of the urban space was used for training and the remaining 30% was used for testing and validation.
LULC Segmentation of RGB Satellite Image Using FCN-8
This work presents use of Fully Convolutional Network (FCN-8) for semantic segmentation of high-resolution RGB earth surface satel-lite images into land use land cover (LULC) categories.
