As the complexity of autonomous vehicles (AVs) continues to increase and artificial
intelligence algorithms are becoming increasingly ubiquitous, a novel safety concern known …

We present a highly compact run-time monitoring approach for deep computer vision
networks that extracts selected knowledge from only a few (down to merely two) hidden …

Trajectory prediction is one of the key components of the autonomous driving software stack.
Accurate prediction for the future movement of surrounding traffic participants is an important …

This paper presents a neural network model for identifying non-human traffic to a website,
which is significantly different from visits made by regular users. Such visits are undesirable …

In domain adaptation, entropy minimization is widely used. However, entropy minimization
will bring negative transfer when the pseudo-labels are inconsistent with the real labels. We …

Аннотация В последнее время возрастает интерес к использованию больших данных
реальной клинической практики для разработки систем искусственного интеллекта в …

Deep neural networks (DNNs) have been widely-adopted in various safety-critical
applications such as computer vision and autonomous driving. However, as technology …

Video anomaly detection is the study of detecting low probability anomalies from high
probability normal behaviour. The imbalance of data raises the need to effectively …

As transformer-based object detection models progress, their impact in critical sectors like
autonomous vehicles and aviation is expected to grow. Soft errors causing bit flips during …

Every ReLU Neural Network (NN) tessellates its input space into activation regions.
Studying this tessellation provides insights into some of the architecture's properties. Recent …