The idea of 'citizen as sensors' has gradually become a reality over the past decade. Today,
Volunteered Geographic Information (VGI) from citizens is highly involved in acquiring …

Emergency situations encompassing natural and human-made disasters, as well as their
cascading effects, pose serious threats to society at large. Machine learning (ML) algorithms …

Visual scene understanding is the core task in making any crucial decision in any computer
vision system. Although popular computer vision datasets like Cityscapes, MS-COCO …

Flood events cause substantial damage to infrastructure and disrupt livelihoods. Timely
monitoring of flood extent helps authorities identify severe impacts and plan relief …

Recent advancements in computer vision and deep learning techniques have facilitated
notable progress in scene understanding, thereby assisting rescue teams in achieving …

Recent research in disaster informatics demonstrates a practical and important use case of
artificial intelligence to save human lives and suffering during natural disasters based on …

Understanding and analyzing human behaviors (actions and interactions of people), voices,
and sounds in chaotic events is crucial in many applications, eg, crowd management …

Natural disasters, such as floods, tornadoes, or wildfires, are increasingly pervasive as the
Earth undergoes global warming. It is difficult to predict when and where an incident will …

In this paper, we present a large-scale hurricane Michael dataset for visual perception in
disaster scenarios, and analyze state-of-the-art deep neural network models for semantic …

Artificial intelligence (AI) is one of the most popular and promising technologies of our time.
While there is a clearer understanding on the role of AI in boosting the efficiencies at private …