Real-world scenarios are usually accompanied by continuously appearing classes with
scare labeled samples, which require the machine learning model to incrementally learn …

Modern networks generate a massive amount of traffic data streams. Analyzing this data is
essential for various purposes, such as network resources management and cyber-security …

Neural networks and deep learning algorithms are designed to function similarly to
biological synaptic structures. However, classical deep learning algorithms fail to fully …

Higher education provides a common educational pattern to all students in colleges and
universities. However, under the general law of higher education, the teaching and …

With the emergence of rich classification models and high computing power, recognition
systems are widely used in various fields. Unfortunately, as the scale of open systems …

Data caps and service degradation are techniques used to control subscribers' data
consumption. These techniques have emerged mainly due to the growing demands placed …

Performance of face detection and recognition is affected and damaged because occlusion
often leads to missed detection. To reduce the recognition accuracy caused by facial …

This article reviews the field of image processing in recent years is enormously developed
and it has been used in several specialties like medical, stand-alone, satellite and the …

In this paper, we present a data augmentation method whose goal is to generate face
images and maximize faces variation in the training set. The main objective is to break free …

Scenarios in which restrictions in data transfer and storage limit the possibility to compose a
single dataset–also exploiting different data sources–to perform a batch-based training …