In humans, Attention is a core property of all perceptual and cognitive operations. Given our
limited ability to process competing sources, attention mechanisms select, modulate, and …

Abstract Machine learning has gained increasing popularity in building energy management
due to its powerful capability and flexibility in model development as well as the rich data …

In this paper, we propose a novel approach to video captioning based on adversarial
learning and long short-term memory (LSTM). With this solution concept, we aim at …

We propose a hierarchically structured reinforcement learning approach to address the
challenges of planning for generating coherent multi-sentence stories for the visual …

We introduce a new task, Video-and-Language Inference, for joint multimodal
understanding of video and text. Given a video clip with aligned subtitles as premise, paired …

Video captioning is the process of describing the content of a sequence of images capturing
its semantic relationships and meanings. Dealing with this task with a single image is …

With the benefits from deep learning technology, generating captions for remote sensing
images has become achievable, and great progress has been made in this field in the …

Abstract Video-and-Language Inference is a recently proposed task for joint video-and-
language understanding. This new task requires a model to draw inference on whether a …

The reduced-order model (ROM) can highly reduce computation costs while maintaining
high high-fidelity performance for model predictive control's application by applying the …

Automatic medical image segmentation is a critical tool for medical image analysis and
disease treatment. In recent years, convolutional neural networks (CNNs) have played an …