Classification of FESEM Images of Nanostructures by Noval Deep Learning Algorithm
RR Patil, GN Jayalaxmi, VH Choudapur, VP Baligar - 2024 - researchsquare.com
Abstract SEM (Scanning Electron Microscopy) takes nanoscale pictures, whereas DL (Deep
Learning) analyses data using neural networks. Image interpretation is streamlined by the …
Learning) analyses data using neural networks. Image interpretation is streamlined by the …
Deep learning, feature learning, and clustering analysis for sem image classification
In this paper, we report upon our recent work aimed at improving and adapting machine
learning algorithms to automatically classify nanoscience images acquired by the Scanning …
learning algorithms to automatically classify nanoscience images acquired by the Scanning …
Classifying nanostructured and heterogeneous materials from transmission electron microscopy images using convolutional neural networks
Artificial intelligence and nanotechnology are two areas of science that have changed the
world and made life easier during this last decade. Both fields are undergoing significant …
world and made life easier during this last decade. Both fields are undergoing significant …
Neural network for nanoscience scanning electron microscope image recognition
In this paper we applied transfer learning techniques for image recognition, automatic
categorization, and labeling of nanoscience images obtained by scanning electron …
categorization, and labeling of nanoscience images obtained by scanning electron …
Toward an automatic classification of SEM images of nanomaterials via a deep learning approach
C Ieracitano, F Pantó, N Mammone… - Neural Approaches to …, 2020 - Springer
Nanofibrous materials produced by electrospinning process may exhibit characteristic
localized defects and anomalies (ie, beads, speck of dust) that make the nanostructure a …
localized defects and anomalies (ie, beads, speck of dust) that make the nanostructure a …
SEM-Net: Deep features selections with Binary Particle Swarm Optimization Method for classification of scanning electron microscope images
G Kavuran - Materials Today Communications, 2021 - Elsevier
Materials Science is increasingly handling artificial intelligence methods to address the
complexity in the field of everyday life necessities. Researchers in both academia and …
complexity in the field of everyday life necessities. Researchers in both academia and …
Enhanced Material Classification via MobileSEMNet: Leveraging MobileNetV2 for SEM Image Analysis.
C Aydin - Traitement du Signal, 2023 - search.ebscohost.com
Background: Scanning electron microscopy (SEM) has been instrumental in elucidating
material details, enabling the use of SEM images for machine learning applications. This …
material details, enabling the use of SEM images for machine learning applications. This …
Classification of Crystal Systems on HAADF STEM Images using Fractal-Based Neural Network
S Dutta, Y Dai, A Rakowski, C Ophus… - Microscopy and …, 2024 - academic.oup.com
Classification of crystal systems for scanning transmission electron microscopy (STEM)
images has been attempted before but often on limited datasets with respect to the number …
images has been attempted before but often on limited datasets with respect to the number …
[PDF][PDF] Image processing of nanostructures
K Anandan - 2009 - getd.libs.uga.edu
The task of image analyzing becomes monumental when one tries to understand,
characterize and extract relevant information from an image. The non-exhaustive list of …
characterize and extract relevant information from an image. The non-exhaustive list of …
Optimized deep networks for the classification of nanoparticles in scanning electron microscopy imaging
The major role of many research studies in nanotechnology is to identify, count, and
measure nanoparticles. Images with particles are often handled by hand, employing a …
measure nanoparticles. Images with particles are often handled by hand, employing a …