Ambient Diagnostics

Cai, Yang; Li, Gregory; Mick, Teri; Chung, Sai Ho; Pham, Binh

doi:10.1007/978-3-540-32263-4_11

Cited by 4 publications

(2 citation statements)

References 30 publications

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“…This method is based on the assumption that the video is from a stationary camera. The heuristic algorithm for segmentation from a moving camera is in reference [9]. Motion creates depth perception that can be used for reconstructing threedimensional objects.…”

Section: Structure From Motionmentioning

confidence: 99%

Learn on the Fly

Cai

2020

Advances in Intelligent Systems and Computing

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In this study, we explore the biologically-inspired Learn-On-The-Fly (LOTF) method that actively learns and discovers patterns with improvisation and sensory intelligence, including pheromone trails, structure from motion, sensory fusion, sensory inhibition, and spontaneous alternation. LOTF is related to classic online modeling and adaptive modeling methods. However, it aims to solve more comprehensive, ill-structured problems such as human activity recognition from a drone video in a disastrous environment. It helps to build explainable AI models that enable human-machine teaming with visual representation, visual reasoning, and machine vision. It is anticipated that LOTF would have an impact on Artificial Intelligence, video analytics for searching and tracking survivors' activities for humanitarian assistance and disaster relief (HADR), field augmented reality, and field robotic swarms.

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Section: Structure From Motionmentioning

confidence: 99%

Learn on the Fly

Cai

2020

Advances in Intelligent Systems and Computing

Self Cite

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show abstract

“…Cross-validation methods [26], [27] and leave one out (LOO) [28], [29] estimator within the deconvolved T-ray data set are utilized to provide a nearly unbiased estimate of the prediction error rate. The performance of classifying the RNA samples are evaluated using eightfold cross-validation, while the powdered material classification is validated using LOO.…”

Section: Performance Assessment Of Classificationmentioning

confidence: 99%