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Found 7 papers, 1 papers with code
Automated Testing of Spatially-Dependent Environmental Hypotheses through Active Transfer Learning
Through this combination it can explore the space of hypothetical inter-quantity relationships and evaluate these hypotheses in real-time, allowing this new knowledge to be immediately exploited for future plans.
Manipulating UAV Imagery for Satellite Model Training, Calibration and Testing
From 33 wide area UAV surveys, 1869 patches were extracted and artificially degraded using an accurate satellite optical model to simulate satellite data.
Automated Aerial Animal Detection When Spatial Resolution Conditions Are Varied
By simulating the PSF, rather than approximating it as a Gaussian, the images were accurately degraded to match the spatial resolution and blurring structure of satellite imagery.
Dataset and Performance Comparison of Deep Learning Architectures for Plum Detection and Robotic Harvesting
Many automated operations in agriculture, such as weeding and plant counting, require robust and accurate object detectors.
Probabilistic Crowd GAN: Multimodal Pedestrian Trajectory Prediction using a Graph Vehicle-Pedestrian Attention Network
Understanding and predicting the intention of pedestrians is essential to enable autonomous vehicles and mobile robots to navigate crowds.
Path Planning in Dynamic Environments using Generative RNNs and Monte Carlo Tree Search
State of the art methods for robotic path planning in dynamic environments, such as crowds or traffic, rely on hand crafted motion models for agents.
Predicting Responses to a Robot's Future Motion using Generative Recurrent Neural Networks
State of the art trajectory prediction models using Recurrent Neural Networks (RNNs) do not currently account for a planned future action of a robot, and so cannot predict how an individual will move in response to a robot's planned path.
