An overview of deep learning methods for image registration with focus on feature-based approaches
K Kuppala, S Banda, TR Barige - … Journal of Image and Data Fusion, 2020 - Taylor & Francis
Image registration is an essential pre-processing step for several computer vision problems
like image reconstruction and image fusion. In this paper, we present a review on image …
like image reconstruction and image fusion. In this paper, we present a review on image …
On the performance of deep transfer learning networks for brain tumor detection using MR images
S Ahmad, PK Choudhury - IEEE Access, 2022 - ieeexplore.ieee.org
A brain tumor need to be identified in its early stage, otherwise it may cause severe
condition that cannot be cured once it is progressed. A precise diagnosis of brain tumor can …
condition that cannot be cured once it is progressed. A precise diagnosis of brain tumor can …
Automatic detection and classification of mammograms using improved extreme learning machine with deep learning
Background and objective Breast cancer, the most intrusive form of cancer affecting women
globally. Next to lung cancer, breast cancer is the one that provides a greater number of …
globally. Next to lung cancer, breast cancer is the one that provides a greater number of …
Efficient deep feature extraction and classification for identifying defective photovoltaic module cells in Electroluminescence images
Electroluminescence (EL) imaging has become the standard test procedure for defect
detection throughout the production, installation and operation stages of solar modules …
detection throughout the production, installation and operation stages of solar modules …
Deep convolutional neural networks architecture for an efficient emergency vehicle classification in real-time traffic monitoring
A Kherraki, R El Ouazzani - IAES International Journal of …, 2022 - search.proquest.com
Nowadays, intelligent transportation system (ITS) has become one of the most popular
subjects of scientific research. ITS provides innovative services to traffic monitoring. The …
subjects of scientific research. ITS provides innovative services to traffic monitoring. The …
[HTML][HTML] On image search in histopathology
Pathology images of histopathology can be acquired from camera-mounted microscopes or
whole-slide scanners. Utilizing similarity calculations to match patients based on these …
whole-slide scanners. Utilizing similarity calculations to match patients based on these …
[PDF][PDF] Convolutional neural network hyper-parameters optimization based on genetic algorithms
S Loussaief, A Abdelkrim - International Journal of …, 2018 - pdfs.semanticscholar.org
In machine learning for computer vision based applications, Convolutional Neural Network
(CNN) is the most widely used technique for image classification. Despite these deep neural …
(CNN) is the most widely used technique for image classification. Despite these deep neural …
[HTML][HTML] Automated systems for detection of COVID-19 using chest X-ray images and lightweight convolutional neural networks
Since December 2019, the appearance of an outbreak of a novel coronavirus disease
namely COVID-19 and which is previously known as 2019-nCoV. COVID-19 is a type of …
namely COVID-19 and which is previously known as 2019-nCoV. COVID-19 is a type of …
Automatic skin lesion segmentation and melanoma detection: Transfer learning approach with u-net and dcnn-svm
Industrial pollution resulting in ozone layer depletion has influenced increased UV radiation
in recent years which is a major environmental risk factor for invasive skin cancer …
in recent years which is a major environmental risk factor for invasive skin cancer …
Discriminative out-of-distribution detection for semantic segmentation
Most classification and segmentation datasets assume a closed-world scenario in which
predictions are expressed as distribution over a predetermined set of visual classes …
predictions are expressed as distribution over a predetermined set of visual classes …