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Found 6 papers, 2 papers with code
Low-Cost Generation and Evaluation of Dictionary Example Sentences
We introduce a new automatic evaluation metric called OxfordEval that measures the win-rate of generated sentences against existing Oxford Dictionary sentences.
DAMSL: Domain Agnostic Meta Score-based Learning
In this paper, we propose Domain Agnostic Meta Score-based Learning (DAMSL), a novel, versatile and highly effective solution that delivers significant out-performance over state-of-the-art methods for cross-domain few-shot learning.
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Cross-Domain Few-Shot
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SB-MTL: Score-based Meta Transfer-Learning for Cross-Domain Few-Shot Learning
Our method, called Score-based Meta Transfer-Learning (SB-MTL), combines transfer-learning and meta-learning by using a MAML-optimized feature encoder and a score-based Graph Neural Network.
Quantifying Urban Canopy Cover with Deep Convolutional Neural Networks
Urban canopy cover is important to mitigate the impact of climate change.
Quantifying Legibility of Indoor Spaces Using Deep Convolutional Neural Networks: Case Studies in Train Stations
Evaluating legibility is particularly desirable in indoor spaces, since it has a large impact on human behavior and the efficiency of space utilization.
Deep Learning Architect: Classification for Architectural Design through the Eye of Artificial Intelligence
Our clustering of architectural designs remarkably corroborates conventional views in architectural history, and the learned architectural features also coheres with the traditional understanding of architectural designs.
