Speech enhancement and speech separation are two related tasks, whose purpose is to
extract either one or more target speech signals, respectively, from a mixture of sounds …

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

Object detection in camera images, using deep learning has been proven successfully in
recent years. Rising detection rates and computationally efficient network structures are …

Despite the remarkable success of deep multi-modal learning in practice, it has not been
well-explained in theory. Recently, it has been observed that the best uni-modal network …

We hypothesize that due to the greedy nature of learning in multi-modal deep neural
networks, these models tend to rely on just one modality while under-fitting the other …

Recent advances in deep learning have shown excellent performance in various scene
understanding tasks. However, in some complex environments or under challenging …

Rice leaf infections are a common hazard to rice production, affecting many farmers all over
the world. Early detection and treatment of rice leaf infection are critical for promoting healthy …

The Internet of Things (IoT) boom has revolutionized almost every corner of people's daily
lives: healthcare, environment, transportation, manufacturing, supply chain, and so on. With …

We present M3ER, a learning-based method for emotion recognition from multiple input
modalities. Our approach combines cues from multiple co-occurring modalities (such as …

Usage of Unmanned Aerial Vehicles (UAVs) is growing rapidly in a wide range of consumer
applications, as they prove to be both autonomous and flexible in a variety of environments …