Pedestrian path prediction is a very challenging problem because scenes are often crowded
or contain obstacles. Existing state-of-the-art long short-term memory (LSTM)-based …

This paper forecasts the future spread of COVID-19 by exploiting the identified lead-lag
effects between different countries. Specifically, we first determine the past relation among …

This article presents a multimodal dataset comprising various representations and
annotations of Franz Schubert's song cycle Winterreise. Schubert's seminal work constitutes …

Music can be described and represented in many different ways, including as sheet music,
symbolic representations, and audio recordings (Müller, 2015). For each of these …

Several MIR applications require fine-grained note alignments between MIDI performances
and their musical scores for training and evaluation. However, large and high-quality …

In this work, we address the novel and rarely considered source separation task of
decomposing piano concerto recordings into separate piano and orchestral tracks. Being a …

Time series data analysis algorithms have been gaining significant importance in the
research community. Extensive studies have confirmed that Dynamic Time War** (DTW) …

The piano concerto is a genre of central importance in Western classical music, often
consisting of a virtuoso solo part for piano and an orchestral accompaniment. In this article …

The interactions among automation configuration rule data have led to undesired and
insecure issues in smart homes, which are known as interactive threats. Most existing …

IoT devices provide users with great convenience in smart homes. However, the
interdependent behaviors across devices may yield unexpected interactions. To analyze the …