Human-in-the-loop active learning via brain computer interface

• Published in: Annals of mathematics and artificial intelligence Vol. 88; no. 11-12; pp. 1191 - 1205
• Main Authors: Netzer, Eitan, Geva, Amir B.
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.12.2020; Springer; Springer Nature B.V
• Subjects: Active learning; Algorithms; Analysis; Annotations; Artificial Intelligence; Artificial neural networks; Cognition; Complex Systems; Computer Science; Computer vision; Deep learning; Electroencephalography; Human-computer interface; Industrial research; Machine learning; Machine vision; Marking; Mathematics; Neural networks; Rapid serial visual presentation; Research projects; S696 Cognition and Neurocomputation; Supervised learning; Deep learning; Transfer Learning; Brain Computer Interface; Human-In-The-Loop; EEG; Clustering; Active Learning

This paper develops and examines an innovative methodology for training an artificial neural network to identify and tag target visual objects in a given database. While the field of Artificial Intelligence in general, and computer vision in particular, has greatly advanced in recent years, fast and...