One of the most promising techniques used in various sciences is deep neural networks
(DNNs). A special type of DNN called a convolutional neural network (CNN) consists of …

The recent advancements in security approaches have significantly increased the ability to
identify and mitigate any type of threat or attack in any network infrastructure, such as a …

Abstract Model inversion (MI) attacks aim to infer and reconstruct private training data by
abusing access to a model. MI attacks have raised concerns about the leaking of sensitive …

In this paper we address the limitations of the DETR-based semi-supervised object detection
(SSOD) framework particularly focusing on the challenges posed by the quality of object …

Background The development of fast, efficient, accurate, and reliable techniques and
methods for food authenticity identification is crucial for food quality assurance. Traditional …

Lost circulation has become a crucial technical problem that restricts the quality and
efficiency improvement of the drilling operation in deep oil and gas wells. The lost-circulation …

Over the decades, Artificial Intelligence (AI) and machine learning has become a
transformative solution in many sectors, services, and technology platforms in a wide range …

Corn is an important part of the Mexican diet. The crop requires constant monitoring to
ensure production. For this, plant density is often used as an indicator of crop yield, since …

Enzyme commission (EC) numbers, which associate a protein sequence with the
biochemical reactions it catalyzes, are essential for the accurate understanding of enzyme …

Convolutional neural network (CNN) comprises the most common and extensively used
network in the field of deep learning (DL). The design of CNNs was influenced by neurons …