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Objective Evaluation-based High-efficiency Learning Framework for Hyperspectral Image Classification
This framework comprises two main parts: (i) a leakage-free balanced sampling strategy, and (ii) a modified end-to-end fully convolutional network (FCN) architecture that optimizes the trade-off between accuracy and efficiency.
Hyperspectral Image Classification
Vocal Bursts Intensity Prediction
Meta-Learning across Meta-Tasks for Few-Shot Learning
In this paper, we argue that the inter-meta-task relationships should be exploited and those tasks are sampled strategically to assist in meta-learning.
