Physics-informed computer vision: A review and perspectives
The incorporation of physical information in machine learning frameworks is opening and
transforming many application domains. Here the learning process is augmented through …
transforming many application domains. Here the learning process is augmented through …
Boosting self-supervised learning via knowledge transfer
In self-supervised learning one trains a model to solve a so-called pretext task on a dataset
without the need for human annotation. The main objective, however, is to transfer this …
without the need for human annotation. The main objective, however, is to transfer this …
Deep convolutional neural network-based approaches for face recognition
S Almabdy, L Elrefaei - Applied Sciences, 2019 - mdpi.com
Face recognition (FR) is defined as the process through which people are identified using
facial images. This technology is applied broadly in biometrics, security information …
facial images. This technology is applied broadly in biometrics, security information …
Imaging through unknown scattering media based on physics-informed learning
Imaging through scattering media is one of the hotspots in the optical field, and impressive
results have been demonstrated via deep learning (DL). However, most of the DL …
results have been demonstrated via deep learning (DL). However, most of the DL …
[HTML][HTML] Deep face recognition using imperfect facial data
A Elmahmudi, H Ugail - Future Generation Computer Systems, 2019 - Elsevier
Today, computer based face recognition is a mature and reliable mechanism which is being
practically utilised for many access control scenarios. As such, face recognition or …
practically utilised for many access control scenarios. As such, face recognition or …
Deep learning-based intelligent face recognition in IoT-cloud environment
In recent years, the Internet-of-Things (IoT) technology is being used in many application
areas such as healthcare, video surveillance, transportation etc. The massive adoption and …
areas such as healthcare, video surveillance, transportation etc. The massive adoption and …
Genetic programming with image-related operators and a flexible program structure for feature learning in image classification
Feature extraction is essential for solving image classification by transforming low-level pixel
values into high-level features. However, extracting effective features from images is …
values into high-level features. However, extracting effective features from images is …
Genetic programming for feature extraction and construction in image classification
Genetic Programming (GP) has been successfully applied to image classification and
achieved promising results. However, most existing methods either address binary image …
achieved promising results. However, most existing methods either address binary image …
Learning-based method to reconstruct complex targets through scattering medium beyond the memory effect
Strong scattering medium brings great difficulties to image objects. Optical memory effect
makes it possible to image through strong random scattering medium in a limited angle field …
makes it possible to image through strong random scattering medium in a limited angle field …
Genetic programming with a new representation to automatically learn features and evolve ensembles for image classification
Image classification is a popular task in machine learning and computer vision, but it is very
challenging due to high variation crossing images. Using ensemble methods for solving …
challenging due to high variation crossing images. Using ensemble methods for solving …