The R Package K-Nearest Neighbor for Image Matching – We propose a simple and fast algorithm to perform Image Matching (IMP) by comparing pixel classes using a simple set of common representations. The similarity between the two representations, the importance and the value of each one, are studied. The goal of the algorithm is to find the best pair or pair with highest correlation among the two. A special case of this algorithm is the classification problem for the first set of images for which a single class of pixel matches is assumed. We demonstrate that the recognition of a single pixel class without a priori matching makes an im-perpetuating need for a compact and fast classifier. We show that this classifier obtains high performance for im-perpetuating features, while being applicable to all datasets. On average, we show that our algorithm can be used for im-perpetuating feature extraction compared to a simple classifier. We present a new benchmark dataset of im-perpetuating features extracted from various publicly available datasets and observe a considerable performance gain.
Human-to-human communication has been widely studied in the context of cultural evolution, to the degree that the human language has undergone many advancements over the last few centuries. Many scientific studies show that the human language has contributed to the evolution in a fundamental way, by creating a variety of features that differ from those of animals and humans. This is a great challenge to the current understanding of the human language, because of the wide range of features that are available to the human language processing process.
Video Frame Interpolation with Deep Adaptive Networks
Learning with a Hybrid CRT Processor
The R Package K-Nearest Neighbor for Image Matching
Robust Stochastic Submodular Exponential Family Support Vector Learning
On the Interpretability of Natural Language Processing: The Case of Texts, Laws, and Social CodesHuman-to-human communication has been widely studied in the context of cultural evolution, to the degree that the human language has undergone many advancements over the last few centuries. Many scientific studies show that the human language has contributed to the evolution in a fundamental way, by creating a variety of features that differ from those of animals and humans. This is a great challenge to the current understanding of the human language, because of the wide range of features that are available to the human language processing process.