LU102496B1 - Facial expression recognition method based on attention mechanism - Google Patents
Facial expression recognition method based on attention mechanism Download PDFInfo
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- LU102496B1 LU102496B1 LU102496A LU102496A LU102496B1 LU 102496 B1 LU102496 B1 LU 102496B1 LU 102496 A LU102496 A LU 102496A LU 102496 A LU102496 A LU 102496A LU 102496 B1 LU102496 B1 LU 102496B1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/174—Facial expression recognition
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/25—Fusion techniques
- G06F18/253—Fusion techniques of extracted features
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/46—Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features
- G06V10/462—Salient features, e.g. scale invariant feature transforms [SIFT]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
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- Software Systems (AREA)
- Biomedical Technology (AREA)
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- Oral & Maxillofacial Surgery (AREA)
- Human Computer Interaction (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Bioinformatics & Cheminformatics (AREA)
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Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202011207089.0A CN112257647A (zh) | 2020-11-03 | 2020-11-03 | 基于注意力机制的人脸表情识别方法 |
Publications (1)
Publication Number | Publication Date |
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LU102496B1 true LU102496B1 (en) | 2021-08-09 |
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Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
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LU102496A LU102496B1 (en) | 2020-11-03 | 2021-02-08 | Facial expression recognition method based on attention mechanism |
Country Status (2)
Country | Link |
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CN (1) | CN112257647A (zh) |
LU (1) | LU102496B1 (zh) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20220406091A1 (en) * | 2021-06-16 | 2022-12-22 | Sony Group Corporation | Landmark detection using deep neural network with multi-frequency self-attention |
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CN112784764B (zh) * | 2021-01-27 | 2022-07-12 | 南京邮电大学 | 一种基于局部与全局注意力机制的表情识别方法及系统 |
CN113033310A (zh) * | 2021-02-25 | 2021-06-25 | 北京工业大学 | 一种基于视觉自注意力网络的表情识别方法 |
CN113076890B (zh) * | 2021-04-09 | 2022-07-29 | 南京邮电大学 | 基于改进的通道注意力机制的人脸表情识别方法及系统 |
CN113111779A (zh) * | 2021-04-13 | 2021-07-13 | 东南大学 | 基于注意力机制的表情识别方法 |
CN113255530B (zh) * | 2021-05-31 | 2024-03-29 | 合肥工业大学 | 基于注意力的多通道数据融合网络架构及数据处理方法 |
CN113223181B (zh) * | 2021-06-02 | 2022-12-23 | 广东工业大学 | 一种弱纹理物体位姿估计方法 |
CN113486744B (zh) * | 2021-06-24 | 2023-02-14 | 中国科学院西安光学精密机械研究所 | 基于眼动和人脸表情范式的学生学习状态评估系统及方法 |
CN113570035B (zh) * | 2021-07-07 | 2024-04-16 | 浙江工业大学 | 一种利用多层卷积层信息的注意力机制方法 |
CN113688204B (zh) * | 2021-08-16 | 2023-04-25 | 南京信息工程大学 | 一种利用相似场景及混合注意力的多人会话情感预测方法 |
CN114821704B (zh) * | 2022-03-16 | 2024-05-24 | 桂林理工大学 | 一种基于关键点注意力机制的口罩人脸识别方法 |
CN114943998A (zh) * | 2022-05-24 | 2022-08-26 | 安徽工业技术创新研究院六安院 | 一种基于结构张量特征和自注意力机制的婴儿表情识别方法 |
CN115439912A (zh) * | 2022-09-20 | 2022-12-06 | 支付宝(杭州)信息技术有限公司 | 一种识别表情的方法、装置、设备及介质 |
CN115294483A (zh) * | 2022-09-28 | 2022-11-04 | 山东大学 | 输电线路复杂场景的小目标识别方法及系统 |
CN116152890B (zh) * | 2022-12-28 | 2024-01-26 | 北京融威众邦电子技术有限公司 | 一种医疗费用自助支付系统 |
CN116311192B (zh) * | 2023-05-15 | 2023-08-22 | 中国科学院长春光学精密机械与物理研究所 | 空间目标定位、区域超分辨重建及类型识别的系统及方法 |
CN116645716B (zh) * | 2023-05-31 | 2024-01-19 | 南京林业大学 | 基于局部特征和全局特征的表情识别方法 |
CN116740795B (zh) * | 2023-08-16 | 2023-11-24 | 天津师范大学 | 基于注意力机制的表情识别方法、模型及模型训练方法 |
CN117912086B (zh) * | 2024-03-19 | 2024-05-31 | 中国科学技术大学 | 基于撒切尔效应驱动的人脸识别方法、系统、设备及介质 |
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2020
- 2020-11-03 CN CN202011207089.0A patent/CN112257647A/zh not_active Withdrawn
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2021
- 2021-02-08 LU LU102496A patent/LU102496B1/en active IP Right Grant
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20220406091A1 (en) * | 2021-06-16 | 2022-12-22 | Sony Group Corporation | Landmark detection using deep neural network with multi-frequency self-attention |
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