Recent advancements in signal processing and computer vision are largely due to machine
learning (ML). While exciting, the reality is that most modern ML approaches are based on …

Automatic object detection is one of the most common and fundamental tasks in
computational intelligence (CI). Neural networks (NNs) are now often the tool of choice for …

Datasets with accurate ground truth from unmanned aerial vehicles (UAV) are cost and time
prohibitive. This is a problem as most modern machine learning (ML) algorithms are based …

Modern supervised machine learning for electro-optical and infrared imagery is based on
data-driven learning of features and decision making. State-of-the-art algorithms are largely …

Accidents and attacks that involve chemical, biological, radiological/nuclear or explosive
(CBRNE) substances are rare, but can be of high consequence. Since the investigation of …

Autonomous robotics and artificial intelligence techniques can be used to support human
personnel in the event of critical incidents. These incidents can pose great danger to human …

Fire detection is a critical component of the Environmental Control and Life Support System
(ECLSS) on board space habitats and remains an important research area with …

Numerous real-world applications require the intelligent combining of disparate information
streams from sensors to create a more complete and enhanced observation in support of …

Recent progress has been made on an explosive laser standoff detection system called
TREDS-2 constructed from COTS components. The TREDS-2 system utilizes combination of …

In order to achieve state of the art classification and detection performance with modern
deep learning approaches, large amounts of labeled data are required. In the infrared (IR) …