Deep learning architectures are now pervasive and filled almost all applications under
image processing, computer vision, and biometrics. The attractive property of feature …

In the field of image processing and computer vision (CV), machine learning (ML)
architectures are widely used. Image compression problems can be solved using …

We propose a joint source and channel coding (JSCC) technique for wireless image
transmission that does not rely on explicit codes for either compression or error correction; …

The extensive use of images in many fields increased the demand for image compression
algorithms to overcome the transfer bandwidth and storage limitations. With image …

Abstract Online Signature Verification (OSV) techniques have been deployed in production
systems for decades, yet training the model for efficient classification of the test signature …

We propose a new 'Bi-Reduced Space'approach to solving 3D Variational Data Assimilation
using Convolutional Autoencoders. We prove that our approach has the same solution as …

In recent years images have been used widely by online social networks providers or
numerous organizations such as governments, police departments, colleges, universities …

Although increasing hidden layers can improve the ability of a neural network in modeling
complex nonlinear relationships, deep layers may result in degradation of accuracy due to …

Semantic segmentation is a fundamental means of extracting information from remotely
sensed images at the pixel level. Deep learning has enabled considerable improvements in …

Artificial intelligence represents a new frontier in human medicine that could save more lives
and reduce the costs, thereby increasing accessibility. As a consequence, the rate of …