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Semantic Pruning for Single Class Interpretability
Convolutional Neural Networks (CNN) have achieved state-of-the-art performance in different computer vision tasks, but at a price of being computationally and power intensive.
Skeleton-Based Human Action Recognition with Global Context-Aware Attention LSTM Networks
In this paper, we propose a new class of LSTM network, Global Context-Aware Attention LSTM (GCA-LSTM), for skeleton based action recognition.
Ranked #62 on
Skeleton Based Action Recognition
on NTU RGB+D 120
On Minimal Accuracy Algorithm Selection in Computer Vision and Intelligent Systems
In this paper we discuss certain theoretical properties of algorithm selection approach to image processing and to intelligent system in general.
Reasoning and Algorithm Selection Augmented Symbolic Segmentation
That is, let there be a set A of available algorithms for symbolic segmentation, a set of input features $F$, a set of image attribute $\mathbb{A}$ and a selection mechanism $S(F,\mathbb{A}, A)$ that selects on a case by case basis the best algorithm.
Symbolic Segmentation Using Algorithm Selection
In this paper we present an alternative approach to symbolic segmentation; instead of implementing a new method we approach symbolic segmentation as an algorithm selection problem.
