標(biāo)題: Titlebook: Emotion Recognition and Understanding for Emotional Human-Robot Interaction Systems; Luefeng Chen,Min Wu,Kaoru Hirota Book 2021 The Editor [打印本頁] 作者: 稀少 時(shí)間: 2025-3-21 17:58
書目名稱Emotion Recognition and Understanding for Emotional Human-Robot Interaction Systems影響因子(影響力)
書目名稱Emotion Recognition and Understanding for Emotional Human-Robot Interaction Systems影響因子(影響力)學(xué)科排名
書目名稱Emotion Recognition and Understanding for Emotional Human-Robot Interaction Systems網(wǎng)絡(luò)公開度
書目名稱Emotion Recognition and Understanding for Emotional Human-Robot Interaction Systems網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Emotion Recognition and Understanding for Emotional Human-Robot Interaction Systems被引頻次
書目名稱Emotion Recognition and Understanding for Emotional Human-Robot Interaction Systems被引頻次學(xué)科排名
書目名稱Emotion Recognition and Understanding for Emotional Human-Robot Interaction Systems年度引用
書目名稱Emotion Recognition and Understanding for Emotional Human-Robot Interaction Systems年度引用學(xué)科排名
書目名稱Emotion Recognition and Understanding for Emotional Human-Robot Interaction Systems讀者反饋
書目名稱Emotion Recognition and Understanding for Emotional Human-Robot Interaction Systems讀者反饋學(xué)科排名
作者: DECRY 時(shí)間: 2025-3-21 20:25
Book 2021acial expression/speech/gesture and their multimodal emotion recognition) and emotion intention understanding, and presents the design and application examples of emotional HRI systems. Aiming at the development needs of emotional robots and emotional human–robot interaction (HRI) systems, this book作者: Pseudoephedrine 時(shí)間: 2025-3-22 03:39
Vertebrate Eye Gene Regulatory Networks, then the low-level expression features are extracted by using principal component analysis. Finally, the high-level expression semantic features are extracted and recognized by WACNN which is optimized by HGA.作者: BOAST 時(shí)間: 2025-3-22 07:25
Weight-Adapted Convolution Neural Network for Facial Expression Recognition, then the low-level expression features are extracted by using principal component analysis. Finally, the high-level expression semantic features are extracted and recognized by WACNN which is optimized by HGA.作者: antenna 時(shí)間: 2025-3-22 10:57 作者: CAPE 時(shí)間: 2025-3-22 13:07 作者: CAPE 時(shí)間: 2025-3-22 18:38
1860-949X al and algorithmic issues.Discusses implementations and caseThis book focuses on the key technologies and scientific problems involved in emotional robot systems, such as multimodal emotion recognition (i.e., facial expression/speech/gesture and their multimodal emotion recognition) and emotion inte作者: Devastate 時(shí)間: 2025-3-22 22:40 作者: Estimable 時(shí)間: 2025-3-23 03:29 作者: 有機(jī)體 時(shí)間: 2025-3-23 05:31 作者: 不能仁慈 時(shí)間: 2025-3-23 12:08
Emotion-Age-Gender-Nationality Based Intention Understanding Using Two-Layer Fuzzy Support Vector Rge, gender, and nationality. It aims to realize the transparent communication by understanding customers’ order intentions at a bar, in such a way that the social relationship between bar staffs and customers becomes smooth.作者: crucial 時(shí)間: 2025-3-23 15:33
https://doi.org/10.1007/978-94-009-5729-9ime, in order to verify the emotional intention understanding model proposed in this chapter, two reasonable scenarios are set up to realize the understanding of emotional intention in specific situations.作者: 圓錐 時(shí)間: 2025-3-23 21:00
978-3-030-61579-6The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: FANG 時(shí)間: 2025-3-24 00:27
Emotion Recognition and Understanding for Emotional Human-Robot Interaction Systems978-3-030-61577-2Series ISSN 1860-949X Series E-ISSN 1860-9503 作者: MAIZE 時(shí)間: 2025-3-24 02:25 作者: ENACT 時(shí)間: 2025-3-24 07:50
Vertebrate Eye Gene Regulatory Networks,on. It aims to make good use of the convolution neural network’s potential performance in avoiding local optimal and speeding up convergence by hybrid genetic algorithm (HGA) with optimal initial population, in such a way that it realizes deep and global emotion understanding in human-robot interact作者: 領(lǐng)導(dǎo)權(quán) 時(shí)間: 2025-3-24 10:52
Thomas Kruse,Hauke Smidt,Ute Lechnerms. One is that feature extraction relies on personalized features. The other is that emotion recognition doesn’t consider the differences among different categories of people. In the proposal, personalized and non-personalized features are fused for speech emotion recognition. High dimensional emot作者: 寒冷 時(shí)間: 2025-3-24 17:23
Modeling Methylaluminoxane (MAO)alities, which not only can extract discriminative emotion features which contain spatio-temporal information, but can also effectively fuse facial expression and speech modalities. Moreover, the proposal is able to handle situations where the contributions of each modality data to emotion recogniti作者: 鼓掌 時(shí)間: 2025-3-24 20:17 作者: 供過于求 時(shí)間: 2025-3-25 00:42 作者: Intuitive 時(shí)間: 2025-3-25 06:26
https://doi.org/10.1007/978-94-011-6893-9ding to facial expression, and emotional intention understanding is obtained mainly based on human emotions and identification information. It aims to make robots capable of recognizing and understanding human emotions, in such a way that make humanrobot interaction run smoothly.作者: 使成整體 時(shí)間: 2025-3-25 09:05 作者: 不溶解 時(shí)間: 2025-3-25 13:45 作者: LASH 時(shí)間: 2025-3-25 16:32 作者: 相一致 時(shí)間: 2025-3-25 21:33
Federalism, Failure and SuccessHuman-robot interaction technology has gradually shifted from computer-centered to human-centered, as natural human-robot interaction has become a new direction of human-robot interaction technology development.作者: avulsion 時(shí)間: 2025-3-26 01:56 作者: 迅速成長 時(shí)間: 2025-3-26 06:17
Tamejiro Hiyama,Hisashi YamamotoDeep neural network (DNN)?has been used as a learning model for modeling the hierarchical architecture of human brain. However, DNN suffers from problems of learning efficiency and computational complexity.作者: single 時(shí)間: 2025-3-26 09:04
,Die Entwicklung des Dünenindividuum,AdaBoost-KNN?using adaptive feature selection with direct optimization is proposed for dynamic emotion recognition in human-robot interaction, where the real-time dynamic emotion is recognized based on facial expression.作者: Tartar 時(shí)間: 2025-3-26 13:20
Introduction,Human-robot interaction technology has gradually shifted from computer-centered to human-centered, as natural human-robot interaction has become a new direction of human-robot interaction technology development.作者: CHAFE 時(shí)間: 2025-3-26 20:48 作者: 躲債 時(shí)間: 2025-3-27 00:27 作者: archetype 時(shí)間: 2025-3-27 02:57
AdaBoost-KNN with Direct Optimization for Dynamic Emotion Recognition,AdaBoost-KNN?using adaptive feature selection with direct optimization is proposed for dynamic emotion recognition in human-robot interaction, where the real-time dynamic emotion is recognized based on facial expression.作者: 現(xiàn)存 時(shí)間: 2025-3-27 06:21
Luefeng Chen,Min Wu,Kaoru HirotaProvides a comprehensive and up-to-date treatise of the area of emotion recognition and understanding by exposing a spectrum of methodological and algorithmic issues.Discusses implementations and case作者: 讓步 時(shí)間: 2025-3-27 10:02 作者: Largess 時(shí)間: 2025-3-27 13:51 作者: concubine 時(shí)間: 2025-3-27 20:19
https://doi.org/10.1007/978-94-011-6893-9ding to facial expression, and emotional intention understanding is obtained mainly based on human emotions and identification information. It aims to make robots capable of recognizing and understanding human emotions, in such a way that make humanrobot interaction run smoothly.作者: 刻苦讀書 時(shí)間: 2025-3-27 22:48
https://doi.org/10.1007/978-3-662-43074-3 challenge in the study of emotional robot systems. In order to realize a human-robot interaction system with certain emotion recognition and intention understanding, and to establish a natural and harmonious human-robot interaction process, this section proposes a human-robot interaction system scheme based on affective computing.作者: Coterminous 時(shí)間: 2025-3-28 02:34 作者: impale 時(shí)間: 2025-3-28 06:26
Dynamic Emotion Understanding Based on Two-Layer Fuzzy Support Vector Regression-Takagi-Sugeno Modeding to facial expression, and emotional intention understanding is obtained mainly based on human emotions and identification information. It aims to make robots capable of recognizing and understanding human emotions, in such a way that make humanrobot interaction run smoothly.作者: Fracture 時(shí)間: 2025-3-28 12:45 作者: 鐵砧 時(shí)間: 2025-3-28 14:45
Weight-Adapted Convolution Neural Network for Facial Expression Recognition,on. It aims to make good use of the convolution neural network’s potential performance in avoiding local optimal and speeding up convergence by hybrid genetic algorithm (HGA) with optimal initial population, in such a way that it realizes deep and global emotion understanding in human-robot interact作者: nauseate 時(shí)間: 2025-3-28 22:12 作者: 蟄伏 時(shí)間: 2025-3-29 00:54 作者: 健談的人 時(shí)間: 2025-3-29 03:45
Multi-support Vector Machine Based Dempster-Shafer Theory for Gesture Intention Understanding,e Coding (SC) based Speeded-Up Robust Features (SURF)?are used for feature extraction of depth and RGB image. Aiming at the problems of the small sample, high dimensionality and feature redundancy for image data, we use the SURF algorithm to extract the features of the original image, and then perfo作者: Free-Radical 時(shí)間: 2025-3-29 08:31 作者: Facilities 時(shí)間: 2025-3-29 15:02
Dynamic Emotion Understanding Based on Two-Layer Fuzzy Support Vector Regression-Takagi-Sugeno Modeding to facial expression, and emotional intention understanding is obtained mainly based on human emotions and identification information. It aims to make robots capable of recognizing and understanding human emotions, in such a way that make humanrobot interaction run smoothly.作者: Certainty 時(shí)間: 2025-3-29 19:26 作者: 有權(quán)威 時(shí)間: 2025-3-29 20:35
Emotional Human-Robot Interaction Systems,and constructs a set of robot emotion interaction system based on the actual equipment. The interaction system of emotion robot constructed in this chapter provides an experimental platform for the verification of emotion recognition algorithm and emotion intention understanding model. At the same t作者: mitten 時(shí)間: 2025-3-30 03:44
Experiments and Applications of Emotional Human-Robot Interaction Systems, challenge in the study of emotional robot systems. In order to realize a human-robot interaction system with certain emotion recognition and intention understanding, and to establish a natural and harmonious human-robot interaction process, this section proposes a human-robot interaction system sch作者: Dorsal-Kyphosis 時(shí)間: 2025-3-30 06:35 作者: 出生 時(shí)間: 2025-3-30 11:50 作者: hardheaded 時(shí)間: 2025-3-30 16:26
1860-949X ovides readers with the state-of-the-art methods of multimodal emotion recognition, intention understanding, and application examples of emotional HRI systems.978-3-030-61579-6978-3-030-61577-2Series ISSN 1860-949X Series E-ISSN 1860-9503 作者: 創(chuàng)新 時(shí)間: 2025-3-30 18:57
Two-Stage Fuzzy Fusion Based-Convolution Neural Network for Dynamic Emotion Recognition,ing canonical correlation analysis and fuzzy broad learning system, so as to take into account the correlation and difference between different modal features, as well as handle the ambiguity of emotional state information.作者: Ascribe 時(shí)間: 2025-3-30 21:45
Correction to: Dynamic Emotion Understanding Based on Two-Layer Fuzzy Support Vector Regression-Tak.
