Search Results for author:
Found 8 papers, 4 papers with code
MSMatch: Semi-Supervised Multispectral Scene Classification with Few Labels
The trained neural network achieves state-of-the-art results on EuroSAT with an accuracy that is up to 19. 76% better than previous methods depending on the number of labeled training examples.
Ranked #5 on
Scene Classification
on UC Merced Land Use Dataset
Geodesy of irregular small bodies via neural density fields: geodesyNets
When the body shape information is available, geodesyNets can seamlessly exploit it and be trained to represent a high-fidelity neural density field able to give insights into the internal structure of the body.
Robust Wake-Up Word Detection by Two-stage Multi-resolution Ensembles
It employs two models: a lightweight on-device model for real-time processing of the audio stream and a verification model on the server-side, which is an ensemble of heterogeneous architectures that refine detection.
Speech Enhancement for Wake-Up-Word detection in Voice Assistants
Keyword spotting and in particular Wake-Up-Word (WUW) detection is a very important task for voice assistants.
The Fellowship of the Dyson Ring: ACT&Friends' Results and Methods for GTOC 11
Dyson spheres are hypothetical megastructures encircling stars in order to harvest most of their energy output.
Selected Trends in Artificial Intelligence for Space Applications
The development and adoption of artificial intelligence (AI) technologies in space applications is growing quickly as the consensus increases on the potential benefits introduced.
Investigation of the Robustness of Neural Density Fields
Hence, this work demonstrates that training neural networks for the gravity inversion problem is appropriate as long as the gravity signal is distinguishable from noise.
Machine learning-based identification of Gaia astrometric exoplanet orbits
The third Gaia data release (DR3) contains $\sim$170 000 astrometric orbit solutions of two-body systems located within $\sim$500 pc of the Sun.
