Performance comparison of machine learning driven approaches for classification of complex noises in quick response code images
Quick response codes (QRCs) are found on many consumer products and often encode
security information. However, information retrieval at receiving end may become …
security information. However, information retrieval at receiving end may become …
An efficient machine learning-based model to effectively classify the type of noises in QR code: A hybrid approach
Granting smart device consumers with information, simply and quickly, is what drives quick
response (QR) codes and mobile marketing to go hand in hand. It boosts marketing …
response (QR) codes and mobile marketing to go hand in hand. It boosts marketing …
Denoising of magnetic resonance images of brain tumor using BT-Autonet
While obtaining medical images from sources such as Magnetic Resonance Imaging (MRI),
Computed Tomography (CT), and ultrasound, noise is observed within images obtained …
Computed Tomography (CT), and ultrasound, noise is observed within images obtained …
Facial image noise classification and denoising using neural network
M Tripathi - Sustainable Engineering and Innovation, 2021 - sei.ardascience.com
Image denoising is an important aspect of image processing. Noisy images are produced as
a result of technical and environmental flaws. As a result, it is reasonable to consider image …
a result of technical and environmental flaws. As a result, it is reasonable to consider image …
[PDF][PDF] Deep convolutional neural network for SEM image noise variance classification
Scanning Electron Microscopy (SEM) image plays a significant role in industrial, medical,
and research fields. However, image defects, including existing noise will degrade the …
and research fields. However, image defects, including existing noise will degrade the …
Convolutional neural network-based image denoising for synchronous measurement of temperature and deformation at elevated temperature
Non-contact measurement method at elevated temperatures has been widely studied, which
provides an efficient means for evaluating the properties of high-temperature materials …
provides an efficient means for evaluating the properties of high-temperature materials …
Deep learning optimization for small object classification in lensfree holographic microscopy
Lensfree holographic microscopy is a compact and cost-effective modality for imaging large
fields of view with high resolution. When combined with automated image processing, it can …
fields of view with high resolution. When combined with automated image processing, it can …
Machine learning aided classification of noise distribution in scanning electron microscopy images
Noise estimation is a crucial part of any modern supervised denoiser. Various statistical
approaches are studied to estimate the noise, but generally these depend on a manual …
approaches are studied to estimate the noise, but generally these depend on a manual …
Controllable deep learning denoising model for ultrasound images using synthetic noisy image
M Jiang, C You, M Wang, H Zhang, Z Gao… - Computer Graphics …, 2023 - Springer
Medical ultrasound imaging has gained widespread prevalence in human muscle and
internal organ diagnosis. Nevertheless, various factors such as the interference effect of …
internal organ diagnosis. Nevertheless, various factors such as the interference effect of …
Investigating Digital Illiterate Classification Techniques Based on DeepFace Technology.
DK Shin, TH Kim, DJ Seo, H Kim… - International Journal …, 2024 - search.ebscohost.com
This paper presents an algorithm to identify digital illiterates by analyzing age and emotions
from facial recognition. In this paper, digital illiterates refer to people who struggle in using …
from facial recognition. In this paper, digital illiterates refer to people who struggle in using …