The classification of marine plankton images is of great significance in ecological studies and environmental monitoring. In practical applications, plankton image classification faces several ...

The agent who shot a woman in Minneapolis on Wednesday was pulled about 100 yards by a car last year while firing a stun gun at the driver. By Nicholas Bogel-Burroughs Reporting from Minneapolis The ...

Motor imagery (MI) electroencephalogram (EEG) decoding plays a critical role in brain–computer interfaces but remains challenging due to large inter-subject variability and limited training data.

VLAC is a general-purpose pair-wise critic and manipulation model which designed for real world robot reinforcement learning and data refinement. It provides robust evaluation capabilities for task ...

Meta-MGNN Few-shot graph learning for molecular property prediction WWW 2021 PDF Torch MTA Meta-learning with motif-based task augmentation for few-shot molecular property prediction SDM 2023 PDF [N/A ...

Google Research introduces in-context fine-tuning (ICF) for time-series forecasting named as ‘TimesFM-ICF): a continued-pretraining recipe that teaches TimesFM to exploit multiple related series ...

Department of Materials Science and Engineering, University of Delaware, Newark, Delaware 19716, United States Department of Chemistry, University of Pennsylvania, Philadelphia, Pennsylvania 19104, ...

Abstract: Few-shot learning in image classification aims at learning a model to identify novel categories from a few training samples. Many few-shot learning methods have been proposed to improve the ...

Plant disease recognition technologies have advanced rapidly thanks to deep learning and large annotated datasets, but agricultural applications face unique hurdles. Data collection in the field is ...

Abstract: Although significant progress has been made in few-shot learning, most of existing few-shot image classification methods require supervised pre-training on a large amount of samples of base ...