Object-Shape Recognition Based on Haptic Image
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-319-65289-4_39
Reference25 articles.
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2. Shahabi, C., Kolahdouzan, M.R., Barish, G., Zimmermann, R., Yao, D., Fu, K., Zhang, L.: Alternative techniques for the efficient acquisition of haptic data. In: ACM SIGMETRICS Performance Evaluation Review, vol. 29, no. 1, pp. 334–335. ACM, Berlin (2001)
3. Gao, Y., Hendricks, L.A., Kuchenbecker, K.J., Darrell, T.: Deep learning for tactile understanding from visual and haptic data. In: 2016 IEEE International Conference on Robotics and Automation, pp. 536–543. IEEE (2016)
4. Nakano, T., Uozumi, S., Johansson, R., Ohnishi, K.: A quantization method for haptic data lossy compression. In: 2015 IEEE International Conference on Mechatronics, pp. 126–131. IEEE (2015)
5. Kaneko, T., Ito, S., Sakaino, S., Tsuji, T.: Haptic data compression for rehabilitation databases. In: 13th International Workshop on Advanced Motion Control, pp. 657–662. IEEE (2015)
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