Classifying fishing behavioral diversity using high-frequency movement data

High performance of the support vector machine in classifying hyperspectral data using a limited dataset

To prospect mineral deposits at regional scale, recognition and classification of hydrothermal alteration zones using remote sensing data is a popular strategy. Due to the large number of spectral bands, classification of the hyperspectral data may be negatively affected by the Hughes phenomenon. A practical way to handle the Hughes problem is preparing a lot of training samples until the size ...

Classifying Behavioral Attributes Using Conditional Random Fields

A human behavior recognition method with an application to political speech videos is presented. We focus on modeling the behavior of a subject with a conditional random field (CRF). The unary terms of the CRF employ spatiotemporal features (i.e., HOG3D, STIP and LBP). The pairwise terms are based on kinematic features such as the velocity and the acceleration of the subject. As an exact soluti...

high performance of the support vector machine in classifying hyperspectral data using a limited dataset

to prospect mineral deposits at regional scale, recognition and classification of hydrothermal alteration zones using remote sensing data is a popular strategy. due to the large number of spectral bands, classification of the hyperspectral data may be negatively affected by the hughes phenomenon. a practical way to handle the hughes problem is preparing a lot of training samples until the size ...

A study of persistence of price movement using High Frequency Financial Data

We present a methodology to discover how often the price deviates from established levels without sound reason. We look at the distribution of these so called “rare events” during the trading day and analyze the speed of the price bouncing back to the levels established before the rare events. We provide methods to calibrate trading rules based on the detection of these events and we exemplify ...

Forecasting Volatility using High Frequency Data