Results 61 to 70 of about 371,752 (272)
The study presents biodegradable and recyclable mixed‐matrix membranes (MMMs), hydrogels, and cryogels using luminescent nanoscale metal‐organic frameworks (nMOFs) and biopolymers. These bio‐nMOF‐MMMs combine europium‐based nMOFs as probes for the status of the materials with the biopolymers agar and gelatine and present alternatives to conventional ...
Moritz Maxeiner +4 more
wiley +1 more source
EFFECTIVE MULTI-RESOLUTION TRANSFORM IDENTIFICATION FOR CHARACTERIZATION AND CLASSIFICATION OF TEXTURE GROUPS [PDF]
Texture classification is important in applications of computer image analysis for characterization or classification of images based on local spatial variations of intensity or color.
S. Arivazhagan +2 more
doaj
An Efficient Weakly Supervised Approach for Texture Segmentation via Graph Cuts
We propose an approach for texture segmentation based on weak supervised learning. The weak supervision implies that the user marks only a single small patch for each class in the input image. These patches are used for training.
Bhavsar Arnav V.
doaj +1 more source
Extracting Terrain Texture Features for Landform Classification Using Wavelet Decomposition
Accurate landform classification is a crucial component of geomorphology. Although extensive classification efforts have been exerted based on the terrain factor, the scale analysis to describe the macro and micro landform features still needs standard ...
Yuexue Xu +4 more
doaj +1 more source
Implementation of Drug‐Induced Rhabdomyolysis and Acute Kidney Injury in Microphysiological System
A modular Muscle–Kidney proximal tubule‐on‐a‐chip integrates 3D skeletal muscle and renal proximal tubule tissues to model drug‐induced rhabdomyolysis and acute kidney injury. The coculture system enables dynamic tissue interaction, functional contraction monitoring, and quantification of nephrotoxicity, revealing drug side effect‐induced metabolic ...
Jaesang Kim +4 more
wiley +1 more source
Texture Classification Using Sparse Frame-Based Representations
A new method for supervised texture classification, denoted by frame texture classification method (FTCM), is proposed. The method is based on a deterministic texture model in which a small image block, taken from a texture region, is modeled as a ...
Skretting Karl +1 more
doaj +1 more source
TCvBsISM: Texture Classification via B-Splines-Based Image Statistical Modeling
This paper presents an image statistical modeling-based texture classification (TC) approach via the Bayesian-driven B-splines probability density estimation of the image textural surface appearance (ITSA), termed TCvBsISM.
Jinping Liu +4 more
doaj +1 more source
Scale Selective Extended Local Binary Pattern for Texture Classification
In this paper, we propose a new texture descriptor, scale selective extended local binary pattern (SSELBP), to characterize texture images with scale variations.
AlRegib, Ghassan +2 more
core +1 more source
Herein presented supraparticles combine the nanoparticulate photocatalyst graphitic carbon nitride with the enzyme horseradish peroxidase, which is immobilized on silica nanoparticles. In an optimized compatibility range, both catalysts operate effectively within the hybrid supraparticles and catalyze a cascade reaction consisting of the photocatalytic
Bettina Herbig +11 more
wiley +1 more source
Improving CNN-Based Texture Classification by Color Balancing
Texture classification has a long history in computer vision. In the last decade, the strong affirmation of deep learning techniques in general, and of convolutional neural networks (CNN) in particular, has allowed for a drastic improvement in the ...
Simone Bianco +3 more
doaj +1 more source

