Audio Feature Extraction and Pattern Recognition Introduction Extracting, recognizing, and categorizing features of audio signals (such as genre, tempo, timbre, or mood) are processes that humans perform almost subconsciously. However, audio feature recognition and categorization is largely experience-based. Therefore, the digital implementation of these processes has been largely subjective, b...

semantically, objects in unstructured document are related each other to perform a certain entity relation. This certain entity relation such: drug-drug interaction through their compounds, buyer-seller relationship through the goods or services, etc. Motivated by that kind of interaction, this study proposes a method to extract those objects and their interactions. It is presented a general fr...

In this paper, the impact of demosaicing on gradient extraction is studied and a gradient-based feature pipeline based raw Bayer pattern images proposed. It shown both theoretically experimentally that are applicable to central difference algorithms with negligible performance degradation, as long arrangement color filter array (CFA) patterns matches operators. The constancy assumption, which w...

Group classification rules extraction is an important task in pattern recognition. In this paper, we proposed a classification rules extraction algorithm base on fish swarm optimization. There are two main works in this article: firstly, fish swarm optimization is introduced. Secondly, a classification rules extraction algorithm is proposed. The proposed algorithm provides a good practicability...

feature extraction is a main step in all perceptual image hashing schemes in which robust features will led to better results in perceptual robustness. simplicity, discriminative power, computational efficiency and robustness to illumination changes are counted as distinguished properties of local binary pattern features. in this paper, we investigate the use of local binary patterns for percep...