Results 21 to 30 of about 44,456 (260)

Texture Feature Extraction in Grape Image Classification Using K-Nearest Neighbor

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2022
Indonesian Grapes are a vine. This fruit is often found in markets, shops, roadside. Along with the development of computer technology today, computers can solve problems by classifying objects and objects.
Pulung Nurtantio Andono, Siti Hadiati Nugraini   +1 more
doaj   +1 more source

Hyperspectral Classification Based on Texture Feature Enhancement and Deep Belief Networks

Remote Sensing, 2018
With success of Deep Belief Networks (DBNs) in computer vision, DBN has attracted great attention in hyperspectral classification. Many deep learning based algorithms have been focused on deep feature extraction for classification improvement.
Jiaojiao Li, Bobo Xi, Yunsong Li, Qian Du, Keyan Wang   +4 more
doaj   +1 more source

A Method for Style Transfer from Artistic Images Based on Depth Extraction Generative Adversarial Network

Applied Sciences, 2023
Depth extraction generative adversarial network (DE-GAN) is designed for artistic work style transfer. Traditional style transfer models focus on extracting texture features and color features from style images through an autoencoding network by mixing ...
Xinying Han, Yang Wu, Rui Wan
doaj   +1 more source

Texture Feature Extraction Using Intuitionistic Fuzzy Local Binary Pattern

Journal of Intelligent Systems, 2016
In this paper, intuitionistic fuzzy local binary for texture feature extraction (IFLBP) has been proposed to encode local texture from the input image.
Ansari Mohd Dilshad, Ghrera Satya Prakash, Mishra Arunodaya Raj   +2 more
doaj   +1 more source

AN INGENIOUS TEXTURE AND SHAPE FEATURE EXTRACTION IN REMOTE SENSING IMAGES BY MEANS OF MULTI KERNEL PRINCIPAL COMPONENT ANALYSIS WITH PYRAMIDAL WAVELET TRANSFORM AND CANNY EDGE DETECTION METHOD [PDF]

ICTACT Journal on Image and Video Processing, 2018
In the rapid growth of the digital world, the dealing of remote sensing image is increased day to day in context with the extraction of information. The feature extractions had been an exigent part among the research to classify the remote sensing images
N Balakumar, K Ragul
doaj   +1 more source

The Goertzel Algorithm for the Extraction of Texture Features

IEEE Robotics and Automation Letters
The detection of the properties of objects is essential to deal with the manipulation of objects with artificial hands and grippers. In particular, texture detection is a common challenge in robotics. In the quest for smooth and natural manipulation, response times in the order of milliseconds are needed.
Raúl Lora-Rivera, Óscar Oballe-Peinado, Andrés Trujillo-León, Fernando Vidal-Verdú   +3 more
openaire   +3 more sources

An autoassociator for automatic texture feature extraction [PDF]

Proceedings Fourth International Conference on Computational Intelligence and Multimedia Applications. ICCIMA 2001, 2002
This paper presents an autoassociator neural network for texture feature extraction. Texture features are extracted through the hidden layer of an autoassociator. The Resilient Propagation (RP) algorithm was employed to train the autoassociator with the texture input and output patterns. The performance of the feature extractor was evaluated on Brodatz
S. Kulkarni, B. Verma
openaire   +1 more source

Early Clinical, Imaging, and Pathological Characteristics of SRPK3/TTN‐Digenic Myopathy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective SRPK3/TTN‐digenic myopathy was recently established as a skeletal muscle myopathy caused by digenic inheritance. This study characterizes the early clinical presentation of SRPK3/TTN‐digenic myopathy in one previously reported and seven newly identified pediatric patients.
Rotem Orbach, Sandra Donkervoort, Carola Hedberg‐Oldfors, Giovanni Baranello, Dimah Saade, Precilla D'Souza, Ruchee Patel, Eva Michael, A. Reghan Foley, Diana Bharucha‐Goebel, S. Jin Haugland, Meghan McAnally, Omer Abdul Hamid, Katherine Chao, Ellen F. Macnamara, Alan H. Beggs, Anna Sarkozy, Juliane Mueller, Steven A. Moore, Richard S. Finkel, Cynthia J. Tifft, Francesco Muntoni, Anders Oldfors, Carsten G. Bönnemann   +23 more
wiley   +1 more source

An Improved Two-Step Strategy for Accurate Feature Extraction in Weak-Texture Environments

Sensors
To address the challenge of feature extraction and reconstruction in weak-texture environments, and to provide data support for environmental perception in mobile robots operating in such environments, a Feature Extraction and Reconstruction in Weak ...
Qingjia Lv, Yang Liu, Peng Wang, Xu Zhang, Caihong Wang, Tengsen Wang, Huihui Wang   +6 more
doaj   +1 more source

Multilayer deep feature extraction for visual texture recognition

CoRR, 2022
Convolutional neural networks have shown successful results in image classification achieving real-time results superior to the human level. However, texture images still pose some challenge to these models due, for example, to the limited availability of data for training in several problems where these images appear, high inter-class similarity, the ...
Lucas O. Lyra, Antonio Elias Fabris, João Batista Florindo   +2 more
openaire   +2 more sources