2008 - SPIE Fellow
His primary scientific interests are in Artificial intelligence, Sensor fusion, Computer vision, Situation awareness and Data science. He combines subjects such as Machine learning and Pattern recognition with his study of Artificial intelligence. The concepts of his Sensor fusion study are interwoven with issues in Ontology, Systems design, Information system and Human–computer interaction.
The study incorporates disciplines such as Fictitious play, Cyber-attack, Intrusion detection system, Markov chain and Adaptive control in addition to Situation awareness. He combines subjects such as Information management, Knowledge management, Reasoning system and Logical reasoning with his study of Data science. His research investigates the connection between Image processing and topics such as Image fusion that intersect with problems in Night vision, Pixel, Image segmentation and Algorithm.
Artificial intelligence, Computer vision, Sensor fusion, Situation awareness and Data mining are his primary areas of study. His research in Artificial intelligence intersects with topics in Machine learning and Pattern recognition. His Computer vision study frequently draws connections to adjacent fields such as Radar.
His study connects Identification and Sensor fusion. His Situation awareness study frequently draws connections to other fields, such as Human–computer interaction. His research brings together the fields of Image quality and Image fusion.
Erik Blasch mostly deals with Artificial intelligence, Situation awareness, Computer vision, Machine learning and Image fusion. In his work, Pixel is strongly intertwined with Pattern recognition, which is a subfield of Artificial intelligence. His research on Situation awareness also deals with topics like
His Robot research extends to Computer vision, which is thematically connected. His Machine learning research includes themes of Robustness and Knowledge representation and reasoning. His work deals with themes such as Image quality and Data mining, Identification, which intersect with Image fusion.
Erik Blasch spends much of his time researching Artificial intelligence, Analytics, Data science, Situation awareness and Machine learning. His Artificial intelligence research is multidisciplinary, relying on both Radar, Computer vision and Pattern recognition. Erik Blasch focuses mostly in the field of Computer vision, narrowing it down to matters related to Task analysis and, in some cases, Image fusion.
His studies in Analytics integrate themes in fields like Ontology, Avionics, Collision avoidance, Harm and Security assessment. His study in Data science is interdisciplinary in nature, drawing from both Edge computing, Cloud computing, Focus, Data analysis and Big data. His Situation awareness research is multidisciplinary, incorporating perspectives in Information exchange, Visualization, Space object and Brooks–Iyengar algorithm.
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Encoding Color Information for Visual Tracking: Algorithms and Benchmark
Pengpeng Liang;Erik Blasch;Haibin Ling.
IEEE Transactions on Image Processing (2015)
Objective Assessment of Multiresolution Image Fusion Algorithms for Context Enhancement in Night Vision: A Comparative Study
Z. Liu;E. Blasch;Z. Xue;J. Zhao.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2012)
High-Level Information Fusion Management and System Design
Erik Blasch;Éloi Bossé;Dale Lambert.
Scalable sentiment classification for Big Data analysis using Naïve Bayes Classifier
Bingwei Liu;Erik Blasch;Yu Chen;Dan Shen.
international conference on big data (2013)
Issues and challenges of knowledge representation and reasoning methods in situation assessment (Level 2 Fusion)
Erik Blasch;Ivan Kadar;John Salerno;Mieczyslaw M. Kokar.
Proceedings of SPIE, the International Society for Optical Engineering (2006)
Kalman Filtering with Nonlinear State Constraints
Chun Yang;E. Blasch.
IEEE Transactions on Aerospace and Electronic Systems (2009)
JDL level 5 fusion model: user refinement issues and applications in group tracking
Erik P. Blasch;Susan Plano.
Signal processing, sensor fusion, and target recognition. Conference (2002)
Issues and Challenges in Situation Assessment (Level 2 Fusion)
Erik Blasch;Ivan Kadar;John S. Salerno;Mieczyslaw M. Kokar.
Journal of Advances in Information Fusion (2006)
Revisiting the JDL model for information exploitation
Erik Blasch;Alan Steinberg;Subrata Das;James Llinas.
international conference on information fusion (2013)
DFIG Level 5 (User Refinement) issues supporting Situational Assessment Reasoning
E. Blasch;S. Plano.
international conference on information fusion (2005)
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