Search Results for author:
Found 7 papers, 3 papers with code
TIDE: Test Time Few Shot Object Detection
Few-shot object detection (FSOD) aims to extract semantic knowledge from limited object instances of novel categories within a target domain.
Learning noise-induced transitions by multi-scaling reservoir computing
To capture such stochastic transitions from data, we find that leveraging a machine learning model, reservoir computing as a type of recurrent neural network, can learn noise-induced transitions.
Multi-Agent Reinforcement Learning: Methods, Applications, Visionary Prospects, and Challenges
This paper aims to review methods and applications and point out research trends and visionary prospects for the next decade.
Neural-network solutions to stochastic reaction networks
The stochastic reaction network in which chemical species evolve through a set of reactions is widely used to model stochastic processes in physics, chemistry and biology.
SHREC'22 Track: Sketch-Based 3D Shape Retrieval in the Wild
We define two SBSR tasks and construct two benchmarks consisting of more than 46, 000 CAD models, 1, 700 realistic models, and 145, 000 sketches in total.
Two-Hop Walks Indicate PageRank Order
This paper shows that pairwise PageRank orders emerge from two-hop walks.
A Single-shot-per-pose Camera-Projector Calibration System For Imperfect Planar Targets
Existing camera-projector calibration methods typically warp feature points from a camera image to a projector image using estimated homographies, and often suffer from errors in camera parameters and noise due to imperfect planarity of the calibration target.
