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Deep Metric Learning Based on Scalable Neighborhood Components for Remote Sensing Scene Characterization
(Institute of Electrical and Electronics Engineers, 2020-05-12)
With the development of convolutional neural networks (CNNs), the semantic understanding of remote sensing (RS) scenes has been significantly improved based on their prominent feature encoding capabilities. While many ...
Deep Hashing Based on Class-Discriminated Neighborhood Embedding
(Institute of Electrical and Electronics Engineers, 2020-09-30)
Deep-hashing methods have drawn significant attention during the past years in the field of remote sensing (RS)
owing to their prominent capabilities for capturing the semantics
from complex RS scenes and generating the ...
Graph Relation Network: Modeling Relations Between Scenes for Multilabel Remote-Sensing Image Classification and Retrieval
(IEEE, 2020-08-21)
Due to the proliferation of large-scale remote-sensing (RS) archives with multiple annotations, multilabel RS scene classification and retrieval are becoming increasingly popular. Although some recent deep learning-based ...
Noise-Tolerant Deep Neighborhood Embedding for Remotely Sensed Images With Label Noise
(IEEE, 2021-02-02)
Recently, many deep learning-based methods have been developed for solving remote sensing (RS) scene classification or retrieval tasks. Most of the adopted loss functions for training these models require accurate annotations. ...
High-Rankness Regularized Semi-Supervised Deep Metric Learning for Remote Sensing Imagery
(MDPI, 2020)
Deep metric learning has recently received special attention in the field of remote sensing (RS) scene characterization, owing to its prominent capabilities for modeling distances among RS images based on their semantic ...
Robust Normalized Softmax Loss for Deep Metric Learning-Based Characterization of Remote Sensing Images With Label Noise
(Institute of Electrical and Electronics EngineersIEEE, 2020-12-16)
Most deep metric learning-based image characterization methods exploit supervised information to model the semantic relations among the remote sensing (RS) scenes. Nonetheless, the unprecedented availability of large-scale ...
Study of Convolutional Neural Networks for Global Parametric Motion Estimation on Log-Polar Imagery
(Institute of Electrical and Electronics Engineers, 2020-08-12)
The problem of motion estimation from images has been widely studied in the past. Although
many mature solutions exist, there are still open issues and challenges to be addressed. For instance, in spite of
the well-known ...
TAG: A Tabletop Games Framework
(CEUR Workshop Proceedings, 2020-10-23)
Tabletop games come in a variety of forms, including board
games, card games, and dice games. In recent years, their
complexity has considerably increased, with many components, rules that change dynamically through the ...
Presentación. Lenguajes de programación en perspectiva
(Asociación de Técnicos de Informática (ATI), 2013)
PiCoCo: Pixelwise Contrast and Consistency Learning for Semisupervised Building Footprint Segmentation
(IEEE, 2021-10-11)
Building footprint segmentation from high-resolution
remote sensing (RS) images plays a vital role in urban planning, disaster response, and population density estimation. Convolutional
neural networks (CNNs) have been ...