https://www.easychair.org/publications/preprint/Tlps
Siamese Networks for One Shot Learning using Kernel Based Activation functions
one shot learningsiamese networkskernel based
https://www.easychair.org/publications/preprint/dl1B
Improving Siamese Networks for One-Shot Learning Using Kernel-Based Activation Functions
one shot learningsiamese networks
https://deepai.org/publication/one-shot-learning-for-autonomous-aerial-manipulation
One-shot Learning for Autonomous Aerial Manipulation | DeepAI
Jun 3, 2022 - 06/03/22 - This paper is concerned with learning transferable contact models for aerial manipulation tasks. We investigate a contact-based ap...
one shot learningautonomousaerialmanipulationdeepai
https://www.caltech.edu/about/news/switching-one-shot-learning-brain-46629
Switching On One-Shot Learning in the Brain - www.caltech.edu
Caltech researchers find the brain regions responsible for making snap decisions about cause and effect.
one shot learningthe brainswitching
https://deepai.org/publication/dynamic-spectrum-matching-with-one-shot-learning
Dynamic Spectrum Matching with One-shot Learning | DeepAI
Jun 23, 2018 - 06/23/18 - Convolutional neural networks (CNN) have been shown to provide a good solution for classification problems that utilize data obtai...
one shot learningdynamicspectrummatchingdeepai
https://deepai.org/publication/updatable-siamese-tracker-with-two-stage-one-shot-learning
Updatable Siamese Tracker with Two-stage One-shot Learning | DeepAI
Apr 30, 2021 - 04/30/21 - Offline Siamese networks have achieved very promising tracking performance, especially in accuracy and efficiency. However, they o...
one shot learningtwo stagesiamesetrackerdeepai
https://openreview.net/forum?id=gIJGcGoz44
PreNAS: Preferred One-Shot Learning Towards Efficient Neural Architecture Search | OpenReview
The wide application of pre-trained models is driving the trend of once-for-all training in one-shot neural architecture search (NAS). However, training within...
one shot learningneural architecture searchpreferred