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Found 8 papers, 2 papers with code
Self-Supervised One-Shot Learning for Automatic Segmentation of StyleGAN Images
We propose a framework for the automatic one-shot segmentation of synthetic images generated by a StyleGAN.
An Aligned Multi-Temporal Multi-Resolution Satellite Image Dataset for Change Detection Research
In our dataset, for each of the 60 AOIs that are meant for training, we augment the Planet datacube with temporally parallel datacubes of Landsat and Sentinel images.
maskGRU: Tracking Small Objects in the Presence of Large Background Motions
To overcome these difficulties, we developed the maskGRU framework that uses a weighted sum of the internal hidden state produced by a convGRU and a 3-channel mask of the tracked object's predicted bounding box as the hidden state to be used at the next time step of the underlying convGRU.
Uncertainty, Edge, and Reverse-Attention Guided Generative Adversarial Network for Automatic Building Detection in Remotely Sensed Images
Our overall F1-score on DeepGlobe's challenging dataset is 0. 745.
CheckSoft : A Scalable Event-Driven Software Architecture for Keeping Track of People and Things in People-Centric Spaces
We present CheckSoft, a scalable event-driven software architecture for keeping track of people-object interactions in people-centric applications such as airport checkpoint security areas, automated retail stores, smart libraries, and so on.
Semantic Labeling of Large-Area Geographic Regions Using Multi-View and Multi-Date Satellite Images and Noisy OSM Training Labels
With no human supervision, our IoU scores for the buildings and roads classes are 0. 8 and 0. 64 respectively which are better than state-of-the-art approaches that use OSM labels and that are not completely automated.
A New Stereo Benchmarking Dataset for Satellite Images
Unlike the existing benckmarking datasets, we have also carried out a quantitative evaluation of our groundtruthed disparities using human annotated points in two of the AOIs.
Adaptive Target Recognition: A Case Study Involving Airport Baggage Screening
The computational effort for this fine-tuning for achieving a desired PD/PFA rate is far less than what it would take to create a new classifier with the same overall performance for the new set of threat specifications.
