palmprint recognition is a new biometrics system based on physiological characteristics of the palmprint, which includes rich, stable, and unique features such as lines, points, and texture. texture is one of the most important features extracted from low resolution images. in this paper, a new local descriptor, local composition derivative pattern (lcdp) is proposed to extract smartly stronger...

Palmprint recognition is a new biometrics system based on physiological characteristics of the palmprint, which includes rich, stable, and unique features such as lines, points, and texture. Texture is one of the most important features extracted from low resolution images. In this paper, a new local descriptor, Local Composition Derivative Pattern (LCDP) is proposed to extract smartly stronger...

many researchers adopt local binary pattern for pattern analysis. however, the long histogram created by local binary pattern is not suitable for large-scale facial database. this paper presents a simple facial pattern descriptor for facial expression recognition. local pattern is computed based on local gradient flow from one side to another side through the center pixel in a 3x3 pixels region...

Many researchers adopt Local Binary Pattern for pattern analysis. However, the long histogram created by Local Binary Pattern is not suitable for large-scale facial database. This paper presents a simple facial pattern descriptor for facial expression recognition. Local pattern is computed based on local gradient flow from one side to another side through the center pixel in a 3x3 pixels region...

This article examines the relationship between partisanship and cities’ approaches to climate policy. Do partisan patterns at the local level match patterns at the national level? Whose partisanship matters: that of elected officials, citizens, or other actors? Previous research indicates that constraints created by the federal system dampen the effects of partisanship on many local policies. G...

classical lbp such as complexity and high dimensions of feature vectors that make it necessary to apply dimension reduction processes. in this paper, we introduce an improved lbp algorithm to solve these problems that utilizes fast pca algorithm for reduction of vector dimensions of extracted features. in other words, proffer method (fast pca+lbp) is an improved lbp algorithm that is extracted ...

Memory and computation efficient deep learning architectures are crucial to continued proliferation of machine learning capabilities to new platforms and systems. Binarization of operations in convolutional neural networks has shown promising results in reducing model size and computing efficiency. In this paper, we tackle the problem using a strategy different from the existing literature by p...