Character classification algorithm based on the low-dimensional feature-optimized model

2021 ◽  
Author(s):  
Kun Zhou ◽  
Qianqian Ge ◽  
Cuncun Wei ◽  
Yafeng Li ◽  
Haiyan Ni ◽  
...  
Keyword(s):  
Classification Algorithm ◽  
Optimized Model ◽  
Low Dimensional ◽  
Character Classification

scholarly journals A High Performace of Local Binary Pattern on Classify Javanese Character Classification

2018 ◽  
Vol 5 (1) ◽  
pp. 8 ◽  
Author(s):  
Ajib Susanto ◽  
Daurat Sinaga ◽  
Christy Atika Sari ◽  
Eko Hari Rachmawanto ◽  
De Rosal Ignatius Moses Setiadi
Keyword(s):  
Feature Extraction ◽  
Image Classification ◽  
Local Binary Pattern ◽  
Nearest Neighbor ◽  
Classification Algorithm ◽  
K Nearest Neighbor ◽  
Characteristic Extraction ◽  
Research Objects ◽  
Character Classification

The classification of Javanese character images is done with the aim of recognizing each character. The selected classification algorithm is K-Nearest Neighbor (KNN) at K = 1, 3, 5, 7, and 9. To improve KNN performance in Javanese character written by the author, and to prove that feature extraction is needed in the process image classification of Javanese character. In this study selected Local Binary Patter (LBP) as a feature extraction because there are research objects with a certain level of slope. The LBP parameters are used between [16 16], [32 32], [64 64], [128 128], and [256 256]. Experiments were performed on 80 training drawings and 40 test images. KNN values after combination with LBP characteristic extraction were 82.5% at K = 3 and LBP parameters [64 64].

Thermoelectric Properties of PbSr(Se,Te)-Based Low Dimensional Structures

2000 ◽  
Vol 626 ◽  
Author(s):  
Harald Beyer ◽  
Joachim Nurnus ◽  
Harald Böttner ◽  
Armin Lambrecht ◽  
Lothar Schmitt ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Thermoelectric Properties ◽  
Power Factor ◽  
Evaluation Method ◽  
Interband Transition ◽  
Multiple Quantum Well ◽  
Calculated Data ◽  
Multiple Quantum ◽  
Ir Transmission ◽  
Low Dimensional

ABSTRACTThermoelectric properties of low dimensional structures based on PbTe/PbSrTe-multiple quantum-well (MQW)-structures with regard to the structural dimensions, doping profiles and levels are presented. Interband transition energies and barrier band-gap are determined from IR-transmission spectra and compared with Kronig-Penney calculations. The influence of the data evaluation method to obtain the 2D power factor will be discussed. The thermoelectrical data of our layers show a more modest enhancement in the power factor σS2 compared with former publications and are in good agreement with calculated data from Broido et al. [5]. The maximum allowed doping level for modulation doped MQW structures is determined. Thermal conductivity measurements show that a ZT enhancement can be achieved by reducing the thermal conductivity due to interface scattering. Additionally promising lead chalcogenide based superlattices for an increased 3D figure of merit are presented.

Sign in / Sign up

Export Citation Format

Share Document