scholarly journals A bridge too far for artificial intelligence?: Automatic classification of stanzas in Spanish poetry

2021 ◽  
Author(s):  
Álvaro Pérez Pozo ◽  
Javier Rosa ◽  
Salvador Ros ◽  
Elena González‐Blanco ◽  
Laura Hernández ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Automatic Classification ◽  
Spanish Poetry

Automatic Classification of Wood Texture Using Local Binary Pattern & Fuzzy K-Nearest Neighbor

2014 ◽  
Vol 903 ◽  
pp. 315-320
Author(s):  
Ismail Mohd Khairuddin ◽  
Ali Abuassal ◽  
Ali Abdelrahim ◽  
Amar Faiz Zainal Abidin ◽  
Syahrul Hisham Mohamad ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Local Binary Pattern ◽  
Nearest Neighbor ◽  
Automatic Classification ◽  
Previous Literature ◽  
K Nearest Neighbor

The price of the wood according to the type of wood. Classification of the woods can be done by studying its texture. This paper introduces Fuzzy k Nearest Neighbor to classify 25 types of wood. The woods images have been taken from the Wood Database of the Centre for Artificial Intelligence & Robotics, Universiti Teknologi Malaysia. The features of wood images are extracted using Local Binary Pattern. The results of this paper shows improvement in wood classification compare to the previous literature.

AUTOMATIC CLASSIFICATION OF WELDING FLAWS USING ARTIFICIAL INTELLIGENCE ALGORITHMS

2009 ◽  
Author(s):  
R. Sikora ◽  
T. Chady ◽  
P. Baniukiewicz ◽  
B. Piekarczyk ◽  
Donald O. Thompson ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Automatic Classification

Automatic classification of hyperactive children: Comparing multiple artificial intelligence approaches

2011 ◽  
Vol 498 (3) ◽  
pp. 190-193 ◽  
Author(s):  
Mona Delavarian ◽  
Farzad Towhidkhah ◽  
Shahriar Gharibzadeh ◽  
Parvin Dibajnia
Keyword(s):  
Artificial Intelligence ◽  
Automatic Classification ◽  
Hyperactive Children

Técnicas De Inteligencia Artificial Aplicadas A Pruebas Capilaroscopicas Para La Detección De Enfermedades Autoinmunes Que Comprometen La Circulación Sanguínea

2021 ◽  
Author(s):  
◽  
M. Alvarado
Keyword(s):  
Artificial Intelligence ◽  
Transfer Learning ◽  
Automatic Classification ◽  
Diseased Subject ◽  
Classification Of Images

The main purpose of this paper is the development of an artificial intelligence model for the automatic classification of images, in order to optimize the detection of pathologies through capillaroscopy tests of the nail fold, this technique allows obtaining images of the morphology of the capillaries in the proximal nail fold of the hands. We used a database that consists of 300 images of capillaries corresponding to the nail fold. These images were labeled as healthy or diseased subject depending on the patterns of the capillaries. The method used to classify the images into two classes was transfer learning from a MobileNet V2 base model. The results show that the network is capable of detecting the presence of pathological patterns in the capillaries with a precision of 96.667%.

Interpreting HVEM of muscle-cell impulse networks

1992 ◽  
Vol 50 (1) ◽  
pp. 126-127
Author(s):  
Paul DeCosta ◽  
Kyugon Cho ◽  
Stephen Shemlon ◽  
Heesung Jun ◽  
Stanley M. Dunn
Keyword(s):  
Structural Analysis ◽  
Muscle Cell ◽  
Electron Micrographs ◽  
Relative Size ◽  
Automatic Classification ◽  
Nerve Fibers ◽  
Analysis Algorithm ◽  
Structural Networks

Introduction: The analysis and interpretation of electron micrographs of cells and tissues, often requires the accurate extraction of structural networks, which either provide immediate 2D or 3D information, or from which the desired information can be inferred. The images of these structures contain lines and/or curves whose orientation, lengths, and intersections characterize the overall network.Some examples exist of studies that have been done in the analysis of networks of natural structures. In, Sebok and Roemer determine the complexity of nerve structures in an EM formed slide. Here the number of nodes that exist in the image describes how dense nerve fibers are in a particular region of the skin. Hildith proposes a network structural analysis algorithm for the automatic classification of chromosome spreads (type, relative size and orientation).

Sign in / Sign up

Export Citation Format

Share Document