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Feature selection and neural network architecture evaluation for real-time video object classification.

, , , и . CEC, стр. 1038-1045. IEEE, (2016)

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Andrew Curtis

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Kent Curtis

 

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A method to segment a 3D surface point cloud for selective sensing in robotic exploration., и . ROSE, стр. 152-157. IEEE, (2010)Computational Methods for Selective Acquisition of Depth Measurements in Machine Perception., , и . SMC, стр. 876-881. IEEE, (2013)Computational Methods for Selective Acquisition of Depth Measurements: An Experimental Evaluation., , и . ACIVS, том 8192 из Lecture Notes in Computer Science, стр. 389-401. Springer, (2013)3D Modeling from Multiple Views with Integrated Registration and Data Fusion., , и . CRV, стр. 252-259. IEEE Computer Society, (2009)Feature selection and neural network architecture evaluation for real-time video object classification., , , и . CEC, стр. 1038-1045. IEEE, (2016)A Frequency Domain Approach to Registration Estimation in Three-Dimensional Space., и . IEEE Trans. Instrumentation and Measurement, 57 (1): 110-120 (2008)Estimating optimal regions for improvement in range acquisition from a single point of view., и . ROSE, стр. 198-203. IEEE, (2012)Visual monitoring of surface deformations on objects manipulated with a robotic hand., , и . ROSE, стр. 128-133. IEEE, (2010)A Method for Dynamic Selection of Optimal Depth Measurements Acquisition with Random Access Range Sensors., и . CRV, стр. 311-318. IEEE Computer Society, (2013)Behavior-driven video analytics system for critical infrastructure protection., , , и . CISDA, стр. 1-8. IEEE, (2014)