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一种基于无监督局部度量学习和重排序的行人再识别方法

Номер патента: CN107506703A
Опубликовано: 22-12-2017
Автор(ы): 叶齐祥, 焦建彬, 赵恒�, 韩振军
Принадлежит: University of Chinese Academy of Sciences
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Associating identifiers based on paired data sets

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Using machine learning and/or neural networks to validate stem cells and their derivatives for use in cell therapy, drug discovery, and diagnostics

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Securing blockchain transaction based on undetermined data

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Electronic equipment displaying various kinds of information available by wearing on body

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Multi-party computation system for learning a classifier

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Method and device for generating finite state automata, and recognition method

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A kind of monitoring method for drinking behavior of laboratory mice, and its system and device

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Systems and methods for learning new watermark algorithms for a data processing accelerator

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Generating domain specific language expressions based on images

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Tensorized LSTM with Adaptive Shared Memory for Learning Trends in Multivariate Time Series

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Tensorized lstm with adaptive shared memory for learning trends in multivariate time series

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Apparatus for learning image of vehicle camera and method thereof

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Distributed systems and methods for learning about a bioprocess from redox indicators and local conditions

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Emotion recognition method and system based on heart-expression synchronization

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Electronic device, and voice recognition method of electronic device

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Vehicle Fuel Economy Evaluation Method Based on Data Analysis

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Touch operation recognition method and apparatus, and related device

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Reinforcement learning and nonlinear programming based system design

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Action recognition method and apparatus, terminal device, and motion monitoring system

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System and method for coordinated agent learning and explanation using hierarchical factors

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Image recognition method and device thereof

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Target recognition method and appartus, storage medium, and electronic device

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Activity recognition method, display method, and electronic device

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Motion recognition method and apparatus, terminal device, and sport monitoring system

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