An overview of machine learning within embedded and mobile devices–optimizations and applications
Embedded systems technology is undergoing a phase of transformation owing to the novel
advancements in computer architecture and the breakthroughs in machine learning …
advancements in computer architecture and the breakthroughs in machine learning …
Machine learning techniques in emerging cloud computing integrated paradigms: A survey and taxonomy
Cloud computing offers Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and
Software as a Service (SaaS) to provide compute, network, and storage capabilities to the …
Software as a Service (SaaS) to provide compute, network, and storage capabilities to the …
A survey on application of machine learning for Internet of Things
Abstract Internet of Things (IoT) has become an important network paradigm and there are
lots of smart devices connected by IoT. IoT systems are producing massive data and thus …
lots of smart devices connected by IoT. IoT systems are producing massive data and thus …
First steps toward camera model identification with convolutional neural networks
Detecting the camera model used to shoot a picture enables to solve a wide series of
forensic problems, from copyright infringement to ownership attribution. For this reason, the …
forensic problems, from copyright infringement to ownership attribution. For this reason, the …
Efficient source camera identification with diversity-enhanced patch selection and deep residual prediction
Source camera identification has long been a hot topic in the field of image forensics.
Besides conventional feature engineering algorithms developed based on studying the …
Besides conventional feature engineering algorithms developed based on studying the …
A deep learning approach for iris sensor model identification
The aim of this paper is to propose an algorithm based on convolutional neural networks
(CNN) for iris sensor model identification. This task is important in forensics applications as …
(CNN) for iris sensor model identification. This task is important in forensics applications as …
A survey on digital camera identification methods
J Bernacki - Forensic Science International: Digital Investigation, 2020 - Elsevier
Digital forensics is a topic that has attracted many attention. One of the most common tasks
in digital forensics is imaging sensor identification. It may be understood as recognizing …
in digital forensics is imaging sensor identification. It may be understood as recognizing …
Camera identification based on domain knowledge-driven deep multi-task learning
Camera identification has recently attracted considerable attention in the image forensic
field of research. Several algorithms have been established based on the hand-crafted …
field of research. Several algorithms have been established based on the hand-crafted …
On the vulnerability of deep learning to adversarial attacks for camera model identification
Camera model identification is a fundamental task for many investigative activities, and is
drawing great attention in the research community. In this context, convolutional neural …
drawing great attention in the research community. In this context, convolutional neural …
A preliminary study on convolutional neural networks for camera model identification
Camera model identification is paramount to verify image origin and authenticity in a blind
fashion. State-of-the-art techniques leverage the analysis of features describing …
fashion. State-of-the-art techniques leverage the analysis of features describing …