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Perceiving, Learning, and Recognizing 3D Objects: An Approach to Cognitive Service Robots.

, , , , and . AAAI, page 596-603. AAAI Press, (2018)

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Investigating the Importance of Shape Features, Color Constancy, Color Spaces and Similarity Measures in Open-Ended 3D Object Recognition., , , and . CoRR, (2020)Lifelong 3D object recognition and grasp synthesis using dual memory recurrent self-organization networks., and . Neural Networks, (2022)Object Learning and Grasping Capabilities for Robotic Home Assistants., , , and . RoboCup, volume 9776 of Lecture Notes in Computer Science, page 279-293. Springer, (2016)An orthographic descriptor for 3D object learning and recognition., , , and . IROS, page 4158-4163. IEEE, (2016)Reinforcement Learning with Potential Functions Trained to Discriminate Good and Bad States., , , and . IJCNN, page 1-7. IEEE, (2021)Open-Ended Fine-Grained 3D Object Categorization by Combining Shape and Texture Features in Multiple Colorspaces., and . HUMANOIDS, page 135-141. IEEE, (2021)An interactive open-ended learning approach for 3D object recognition., , , , and . ICARSC, page 47-52. IEEE, (2014)Local-LDA: Open-Ended Learning of Latent Topics for 3D Object Recognition., , and . IEEE Trans. Pattern Anal. Mach. Intell., 42 (10): 2567-2580 (2020)Look Further to Recognize Better: Learning Shared Topics and Category-Specific Dictionaries for Open-Ended 3D Object Recognition.. IROS, page 5438-5443. IEEE, (2019)Learning to Grasp 3D Objects using Deep Residual U-Nets., , and . RO-MAN, page 781-787. IEEE, (2020)