Machine learning–based medical anomaly detection is an important problem that has been
extensively studied. Numerous approaches have been proposed across various medical …

There is currently a huge interest around autonomous vehicles from both industry and
academia. This is mainly due to recent advances in machine learning and deep learning …

Predicting the future trajectories of multiple interacting pedestrians in a scene has become
an increasingly important problem for many different applications ranging from control of …

This paper addresses the problem of path prediction for multiple interacting agents in a
scene, which is a crucial step for many autonomous platforms such as self-driving cars and …

Generating forecasts for time series with multiple seasonal cycles is an important use case
for many industries nowadays. Accounting for the multiseasonal patterns becomes …

Computing trajectory similarities is a critical and fundamental task for various spatial-
temporal applications, such as clustering, prediction, and anomaly detection. Traditional …

Aircraft trajectory prediction is the basis of approach and departure sequencing, conflict
detection and resolution and other air traffic management technologies. Accurate trajectory …

Classification of seizure type is a key step in the clinical process for evaluating an individual
who presents with seizures. It determines the course of clinical diagnosis and treatment, and …

This paper presents a novel deep learning framework for human trajectory prediction and
detecting social group membership in crowds. We introduce a generative adversarial …

Current multi-person localisation and tracking systems have an over reliance on the use of
appearance models for target re-identification and almost no approaches employ a …