Robotics Dexterous Grasping: The Methods Based on Point Cloud and Deep Learning [0.03%]
基于点云和深度学习的机器人灵巧抓取方法研究
Haonan Duan,Peng Wang,Yayu Huang et al.
Haonan Duan et al.
Dexterous manipulation, especially dexterous grasping, is a primitive and crucial ability of robots that allows the implementation of performing human-like behaviors. Deploying the ability on robots enables them to assist and substitute hum...
Alessandro Salatiello,Mohammad Hovaidi-Ardestani,Martin A Giese
Alessandro Salatiello
The ability to make accurate social inferences makes humans able to navigate and act in their social environment effortlessly. Converging evidence shows that motion is one of the most informative cues in shaping the perception of social int...
Shrunken Social Brains? A Minimal Model of the Role of Social Interaction in Neural Complexity [0.03%]
萎缩的社会大脑？社会互动在神经复杂性中的作用的简化模型
Georgina Montserrat Reséndiz-Benhumea,Ekaterina Sangati,Federico Sangati et al.
Georgina Montserrat Reséndiz-Benhumea et al.
The social brain hypothesis proposes that enlarged brains have evolved in response to the increasing cognitive demands that complex social life in larger groups places on primates and other mammals. However, this reasoning can be challenged...
Spiking Neural Network for Fourier Transform and Object Detection for Automotive Radar [0.03%]
汽车雷达傅立叶变换和目标检测的脉冲神经网络
Javier López-Randulfe,Tobias Duswald,Zhenshan Bing et al.
Javier López-Randulfe et al.
The development of advanced autonomous driving applications is hindered by the complex temporal structure of sensory data, as well as by the limited computational and energy resources of their on-board systems. Currently, neuromorphic engin...
Rhys Howard,Claudio Zito
Rhys Howard
This paper is concerned with learning transferable forward models for push manipulation that can be applying to novel contexts and how to improve the quality of prediction when critical information is available. We propose to learn a parame...
A Systematic Analysis of Hand Movement Functionality: Qualitative Classification and Quantitative Investigation of Hand Grasp Behavior [0.03%]
手运动功能的系统分析：手握动作行为的定性分类与定量研究
Yuan Liu,Li Jiang,Hong Liu et al.
Yuan Liu et al.
Understanding human hand movement functionality is fundamental in neuroscience, robotics, prosthetics, and rehabilitation. People are used to investigate movement functionality separately from qualitative or quantitative perspectives. Howev...
BEAN: Interpretable and Efficient Learning With Biologically-Enhanced Artificial Neuronal Assembly Regularization [0.03%]
基于生物增强的人工神经元集合正则化的可解释高效学习方法
Yuyang Gao,Giorgio A Ascoli,Liang Zhao
Yuyang Gao
Deep neural networks (DNNs) are known for extracting useful information from large amounts of data. However, the representations learned in DNNs are typically hard to interpret, especially in dense layers. One crucial issue of the classical...
Public Opinion Early Warning Agent Model: A Deep Learning Cascade Virality Prediction Model Based on Multi-Feature Fusion [0.03%]
基于多特征融合的深度学习级联舆论预警模型
Liqun Gao,Yujia Liu,Hongwu Zhuang et al.
Liqun Gao et al.
With the rapid popularity of agent technology, a public opinion early warning agent has attracted wide attention. Furthermore, a deep learning model can make the agent more automatic and efficient. Therefore, for the agency of a public opin...
Optimum Integration Procedure for Connectionist and Dynamic Field Equations [0.03%]
连接主义与动态场论方程的最优整合方法
Andrés Rieznik,Rocco Di Tella,Lara Schvartzman et al.
Andrés Rieznik et al.
Connectionist and dynamic field models consist of a set of coupled first-order differential equations describing the evolution in time of different units. We compare three numerical methods for the integration of these equations: the Euler ...
Charles H Moore,Sierra F Corbin,Riley Mayr et al.
Charles H Moore et al.
Upper-limb prostheses are subject to high rates of abandonment. Prosthesis abandonment is related to a reduced sense of embodiment, the sense of self-location, agency, and ownership that humans feel in relation to their bodies and body part...