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Found 6 papers, 2 papers with code
A Nearest Neighbor Network to Extract Digital Terrain Models from 3D Point Clouds
When 3D-point clouds from overhead sensors are used as input to remote sensing data exploitation pipelines, a large amount of effort is devoted to data preparation.
Batch-normalized Recurrent Highway Networks
Gradient control plays an important role in feed-forward networks applied to various computer vision tasks.
Semantic Sentence Embeddings for Paraphrasing and Text Summarization
This paper introduces a sentence to vector encoding framework suitable for advanced natural language processing.
A Fully Convolutional Network for Semantic Labeling of 3D Point Clouds
In this paper we present a 1D-fully convolutional network that consumes terrain-normalized points directly with the corresponding spectral data, if available, to generate point-wise labeling while implicitly learning contextual features in an end-to-end fashion.
Algorithms for Semantic Segmentation of Multispectral Remote Sensing Imagery using Deep Learning
In this paper, we adapt state-of-the-art DCNN frameworks in computer vision for semantic segmentation for MSI imagery.
High-Resolution Multispectral Dataset for Semantic Segmentation
Unmanned aircraft have decreased the cost required to collect remote sensing imagery, which has enabled researchers to collect high-spatial resolution data from multiple sensor modalities more frequently and easily.
