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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국정보처리학회 JIPS(Journal of Information Processing Systems) JIPS(Journal of Information Processing Systems) 제17권 제2호
- 발행연도
- 2021.1
- 수록면
- 385 - 398 (14page)
이용수
초록· 키워드
오류제보하기
The complexity of deep learning models affects the real-time performance of gesture recognition, therebylimiting the application of gesture recognition algorithms in actual scenarios. Hence, a residual learning neuralnetwork based on a deep convolutional neural network is proposed. First, small convolution kernels are usedto extract the local details of gesture images. Subsequently, a shallow residual structure is built to share weights,thereby avoiding gradient disappearance or gradient explosion as the network layer deepens; consequently, thedifficulty of model optimisation is simplified. Additional convolutional neural networks are used to acceleratethe refinement of deep abstract features based on the spatial importance of the gesture feature distribution. Finally, a fully connected cascade softmax classifier is used to complete the gesture recognition. Comparedwith the dense connection multiplexing feature information network, the proposed algorithm is optimised infeature multiplexing to avoid performance fluctuations caused by feature redundancy. Experimental resultsfrom the ISOGD gesture dataset and Gesture dataset prove that the proposed algorithm affords a fastconvergence speed and high accuracy.
목차
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참고문헌 (31)
참고문헌 신청
D. Jiang / 2019 / Gesture recognition based on binocular vision / Cluster Computing 22(6):13261~13271
K. Vaesen / 2019 / Integrated 140 GHz FMCW radar for vital sign monitoring and gesture recognition / Microwave Journal 62(6):50~58
X. A. Huang / 2019 / Tracing the motion of finger joints for gesture recognition via sewing RGO-coated fibers onto a textile glove / IEEE Sensors Journal 19(20):9504~9511
J. H. Sun / 2018 / Research on the hand gesture recognition based on deep learning / Proceedings of 2018 12th International Symposium on Antennas, Propagation and EM Theory (ISAPE) :1~4
D. Zhu / 2019 / Individual soldier gesture intelligent recognition system / Proceedings of 2019 IEEE International Conference on Power, Intelligent Computing and Systems (ICPICS) :231~235
K. Vaesen / 2019 / Integrated 140 GHz FMCW radar for vital sign monitoring and gesture recognition / Microwave Journal 62(6):50~58
X. A. Huang / 2019 / Tracing the motion of finger joints for gesture recognition via sewing RGO-coated fibers onto a textile glove / IEEE Sensors Journal 19(20):9504~9511
J. H. Sun / 2018 / Research on the hand gesture recognition based on deep learning / Proceedings of 2018 12th International Symposium on Antennas, Propagation and EM Theory (ISAPE) :1~4
D. Zhu / 2019 / Individual soldier gesture intelligent recognition system / Proceedings of 2019 IEEE International Conference on Power, Intelligent Computing and Systems (ICPICS) :231~235
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