Artificial Intelligence techniques powered by deep neural nets have achieved much success
in several application domains, most significantly and notably in the Computer Vision …

Recognizing human activities from video sequences or still images is a challenging task due
to problems, such as background clutter, partial occlusion, changes in scale, viewpoint …

Abstract Background and Objective: The COVID-19 can cause severe pneumonia and is
estimated to have a high impact on the healthcare system. Early diagnosis is crucial for …

Skin conditions affect 1.9 billion people. Because of a shortage of dermatologists, most
cases are seen instead by general practitioners with lower diagnostic accuracy. We present …

Deep multimodal fusion by using multiple sources of data for classification or regression has
exhibited a clear advantage over the unimodal counterpart on various applications. Yet …

Self-supervised learning methods have witnessed a recent surge of interest after proving
successful in multiple application fields. In this work, we leverage these techniques, and we …

In order to plan a safe maneuver, self-driving vehicles need to understand the intent of other
traffic participants. We define intent as a combination of discrete high level behaviors as well …

Combining machine learning in neural networks with multimodal fusion strategies offers an
interesting potential for classification tasks but the optimum fusion strategies for many …

Forecasting stock prices plays an important role in setting a trading strategy or determining
the appropriate timing for buying or selling a stock. We propose a model, called the feature …

The recent years have witnessed a surge of interests in data analytics with patient Electronic
Health Records (EHR). Data-driven healthcare, which aims at effective utilization of big …