Add to ORKGAs Deep Neural Networks (DNNs) have become an increasingly ubiquitous workload, the range of libraries and tooling available to aid in their development and deployment has grown significantly. Scalable, production quality tools are freely available under permissive licenses, and are accessible enough to enable even small teams to be very productive. However within the research community, awareness and usage of said tools is not necessarily widespread, and researchers may be missing out on potential productivity gains from exploiting the latest tools and workflows. This paper presents a case study where we discuss our recent experience producing an end-to-end artificial intelligence application for industrial defect detection. We detail the ...
In recent years, machine learning (ML) and, more noticeably, deep learning (DL), have be- come incre...
Embedded systems are becoming interconnected and collaborative systems able to perform autonomous ta...
Context: Deep learning has proven to be a valuable component in object detection and classification,...
Invited paperDeep learning with neural networks is applied by an increasing number of people outside...
In recent years, large pre-trained deep neural networks (DNNs) have revolutionized the field of comp...
As Deep Neural Networks (DNNs) are rapidly being adopted within large software systems, software dev...
This extensive experimental research provides strong empirical proof of the revolutionary power of d...
The introduction of robots and automation in industrial processes brought many benefits to manufactu...
Deep learning is overhauling a plethora of applications such as voice assistants, autonomous vehicle...
Anomaly detection describes methods of finding abnormal states, instances or data points that differ...
Nowadays, deep neural networks based software have been widely applied in many areas including safet...
The quality of a manufactured product is a major factor that contributes to the growth, productivit...
We consider real-time safety-critical systems that feature closed-loop interactions between the embe...
Deep Neural Networks (DNNs) are extremely computationally demanding, which presents a large barrier ...
The recent rapid development of deep learning has laid a milestone in industrial Image Anomaly Detec...
In recent years, machine learning (ML) and, more noticeably, deep learning (DL), have be- come incre...
Embedded systems are becoming interconnected and collaborative systems able to perform autonomous ta...
Context: Deep learning has proven to be a valuable component in object detection and classification,...
Invited paperDeep learning with neural networks is applied by an increasing number of people outside...
In recent years, large pre-trained deep neural networks (DNNs) have revolutionized the field of comp...
As Deep Neural Networks (DNNs) are rapidly being adopted within large software systems, software dev...
This extensive experimental research provides strong empirical proof of the revolutionary power of d...
The introduction of robots and automation in industrial processes brought many benefits to manufactu...
Deep learning is overhauling a plethora of applications such as voice assistants, autonomous vehicle...
Anomaly detection describes methods of finding abnormal states, instances or data points that differ...
Nowadays, deep neural networks based software have been widely applied in many areas including safet...
The quality of a manufactured product is a major factor that contributes to the growth, productivit...
We consider real-time safety-critical systems that feature closed-loop interactions between the embe...
Deep Neural Networks (DNNs) are extremely computationally demanding, which presents a large barrier ...
The recent rapid development of deep learning has laid a milestone in industrial Image Anomaly Detec...
In recent years, machine learning (ML) and, more noticeably, deep learning (DL), have be- come incre...
Embedded systems are becoming interconnected and collaborative systems able to perform autonomous ta...
Context: Deep learning has proven to be a valuable component in object detection and classification,...