DeepDynamicHand: A Deep Neural Architecture for Labeling Hand Manipulation Strategies in Video Sources Exploiting Temporal Information
暂无分享,去创建一个
[1] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[2] Oswald Lanz,et al. Convolutional Long Short-Term Memory Networks for Recognizing First Person Interactions , 2017, 2017 IEEE International Conference on Computer Vision Workshops (ICCVW).
[3] Manuel G. Catalano,et al. Simplifying Telerobotics: Wearability and Teleimpedance Improves Human-Robot Interactions in Teleoperation , 2018, IEEE Robotics & Automation Magazine.
[4] N. Otsu. A threshold selection method from gray level histograms , 1979 .
[5] Richard Bowden,et al. A boosted classifier tree for hand shape detection , 2004, Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings..
[6] Yi Li,et al. Robot Learning Manipulation Action Plans by "Watching" Unconstrained Videos from the World Wide Web , 2015, AAAI.
[7] Zhijun Zhang,et al. A Varying-Parameter Convergent-Differential Neural Network for Solving Joint-Angular-Drift Problems of Redundant Robot Manipulators , 2018, IEEE/ASME Transactions on Mechatronics.
[8] Oliver Brock,et al. A novel type of compliant and underactuated robotic hand for dexterous grasping , 2016, Int. J. Robotics Res..
[9] Paolo Dario,et al. A Survey of Glove-Based Systems and Their Applications , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).
[10] Shuai Li,et al. A New Varying-Parameter Convergent-Differential Neural-Network for Solving Time-Varying Convex QP Problem Constrained by Linear-Equality , 2018, IEEE Transactions on Automatic Control.
[11] Edoardo Battaglia,et al. A Synergy-Based Optimally Designed Sensing Glove for Functional Grasp Recognition , 2016, Sensors.
[12] Matteo Bianchi,et al. Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands. , 2016, Physics of life reviews.
[13] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[14] Yoshua Bengio,et al. Gradient-based learning applied to document recognition , 1998, Proc. IEEE.
[15] David Stutz,et al. Neural Codes for Image Retrieval , 2015 .
[16] Trevor Darrell,et al. Caffe: Convolutional Architecture for Fast Feature Embedding , 2014, ACM Multimedia.
[17] John C. Platt,et al. A Convolutional Neural Network Hand Tracker , 1994, NIPS.
[18] Shanxin Yuan,et al. First-Person Hand Action Benchmark with RGB-D Videos and 3D Hand Pose Annotations , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[19] Hermann Ney,et al. Deep Hand: How to Train a CNN on 1 Million Hand Images When Your Data is Continuous and Weakly Labelled , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[20] Nikolaos G. Tsagarakis,et al. Translating Videos to Commands for Robotic Manipulation with Deep Recurrent Neural Networks , 2017, 2018 IEEE International Conference on Robotics and Automation (ICRA).
[21] Yiming Yang,et al. A re-examination of text categorization methods , 1999, SIGIR '99.
[22] Matthew J. Hausknecht,et al. Beyond short snippets: Deep networks for video classification , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[23] H. Haken,et al. A theoretical model of phase transitions in human hand movements , 2004, Biological Cybernetics.
[24] Sanjeev Sofat,et al. Vision Based Hand Gesture Recognition , 2009 .
[25] Rob Fergus,et al. Visualizing and Understanding Convolutional Networks , 2013, ECCV.
[26] Bernt Schiele,et al. What Makes for Effective Detection Proposals? , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[27] Dacheng Tao,et al. Feature fusion for 3D hand gesture recognition by learning a shared hidden space , 2012, Pattern Recognit. Lett..
[28] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[29] Wojciech Zaremba,et al. Learning to Execute , 2014, ArXiv.
[30] Ganesh R. Naik,et al. A Piezoresistive Array Armband With Reduced Number of Sensors for Hand Gesture Recognition , 2020, Frontiers in Neurorobotics.
[31] Razvan Pascanu,et al. On the difficulty of training recurrent neural networks , 2012, ICML.
[32] Nicu Sebe,et al. Deep appearance and motion learning for egocentric activity recognition , 2018, Neurocomputing.
[33] Stefan Ulbrich,et al. Master Motor Map (MMM) — Framework and toolkit for capturing, representing, and reproducing human motion on humanoid robots , 2014, 2014 IEEE-RAS International Conference on Humanoid Robots.
[34] Oliver Brock,et al. Exploitation of environmental constraints in human and robotic grasping , 2015, Int. J. Robotics Res..
[35] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[36] Xilong Qu,et al. Robustness Analysis of a Power-Type Varying-Parameter Recurrent Neural Network for Solving Time-Varying QM and QP Problems and Applications , 2020, IEEE Transactions on Systems, Man, and Cybernetics: Systems.
[37] Matteo Bianchi,et al. Recent Data Sets on Object Manipulation: A Survey , 2016, Big Data.
[38] Andrew Zisserman,et al. Deep Face Recognition , 2015, BMVC.
[39] Trevor Darrell,et al. Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation , 2013, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[40] Matteo Bianchi,et al. Synergy-based hand pose sensing: Reconstruction enhancement , 2012, Int. J. Robotics Res..
[41] Charles A. Klein,et al. The nature of drift in pseudoinverse control of kinematically redundant manipulators , 1989, IEEE Trans. Robotics Autom..
[42] Anupam Agrawal,et al. Vision based hand gesture recognition for human computer interaction: a survey , 2012, Artificial Intelligence Review.
[43] Giuseppe Averta,et al. A Synergistic Behavior Underpins Human Hand Grasping Force Control During Environmental Constraint Exploitation , 2018 .
[44] Giuseppe Averta,et al. Postural Hand Synergies during Environmental Constraint Exploitation , 2017, Front. Neurorobot..
[45] Stefan Lee,et al. Lending A Hand: Detecting Hands and Recognizing Activities in Complex Egocentric Interactions , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[46] Oliver Brock,et al. A compact representation of human single-object grasping , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[47] Hanseok Ko,et al. Hidden Markov Model on a unit hypersphere space for gesture trajectory recognition , 2014, Pattern Recognit. Lett..
[48] Stefan Lee,et al. This Hand Is My Hand: A Probabilistic Approach to Hand Disambiguation in Egocentric Video , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops.
[49] Razvan Pascanu,et al. Theano: A CPU and GPU Math Compiler in Python , 2010, SciPy.
[50] Hanqing Lu,et al. EgoGesture: A New Dataset and Benchmark for Egocentric Hand Gesture Recognition , 2018, IEEE Transactions on Multimedia.
[51] Manuel G. Catalano,et al. Toward Dexterous Manipulation With Augmented Adaptive Synergies: The Pisa/IIT SoftHand 2 , 2018, IEEE Transactions on Robotics.
[52] Oliver Brock,et al. A taxonomy of human grasping behavior suitable for transfer to robotic hands , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).
[53] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[54] Giuseppe Averta,et al. From humans to robots: The role of cutaneous impairment in human environmental constraint exploitation to inform the design of robotic hands , 2017, 2017 9th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT).
[55] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[56] Gaël Varoquaux,et al. Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..
[57] Fei-Fei Li,et al. Large-Scale Video Classification with Convolutional Neural Networks , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[58] Gregory D. Hager,et al. Transition state clustering: Unsupervised surgical trajectory segmentation for robot learning , 2017, ISRR.