Autoencoder is an unsupervised learning model, which can automatically learn data
features from a large number of samples and can act as a dimensionality reduction method …

In the Internet-of-Things (IoT) era, billions of sensors and devices collect and process data
from the environment, transmit them to cloud centers, and receive feedback via the Internet …

Face mask detection had seen significant progress in the domains of Image processing and
Computer vision, since the rise of the Covid-19 pandemic. Many face detection models have …

Multi-object tracking (MOT) is an important problem in computer vision which has a wide
range of applications. Formulating MOT as multi-task learning of object detection and re-ID …

Easy access to audio-visual content on social media, combined with the availability of
modern tools such as Tensorflow or Keras, and open-source trained models, along with …

Head pose estimation (HPE) has wide industrial applications, such as online education,
human–robot interaction, and automatic manufacturing. In this article, we address two key …

The free access to large-scale public databases, together with the fast progress of deep
learning techniques, in particular Generative Adversarial Networks, have led to the …

Deep learning has developed as an effective machine learning method that takes in
numerous layers of features or representation of the data and provides state-of-the-art …

Object detection is one of the most important and challenging branches of computer vision,
which has been widely applied in people's life, such as monitoring security, autonomous …

Head pose estimation suffers from several problems, including low pose tolerance under
different disturbances and ambiguity arising from common head pose representation. In this …