Titlebook: Artificial Intelligence and Mobile Services – AIMS 2021; 10th International C Yi Pan,Zhi-Hong Mao,Liang-Jie Zhang Conference proceedings 20

impale

A Privacy Knowledge Transfer Method for Clinical Concept Extraction extraction with high privacy requirements. Therefore, to alleviate privacy leakage during the model release phase, this paper propose a knowledge distillation based privacy protection method. The proposed method follows the teacher-student framework and utilizes a novel distillation method for sequ

BET

有常識(shí)

intertwine

LightBERT: A Distilled Chinese BERT Modelpply these models to online systems for their huge amount of parameters and long inference time. Knowledge Distillation is a popular model compression technique, which could achieve considerable model structure compression with limited performance degradation. However, there are currently no knowled

煞費(fèi)苦心

MURAL

Manipulator Posture Estimation Method Based on Multi-eye Vision and Key Point Detectionobot arm control and reduce the immobilization of the control mode. Multiple cameras illuminate the robotic arm to form a multi-eye vision model. At the same time, the HRNet key point detection model detects the key points of the robotic arm in the picture, establishes a space line equation set, and

思考

doxazosin

Federated Learning for?6G Edge Intelligence: Concepts, Challenges and?Solutionsications on edge computing units, formulating an ubiquitous “Edge Intelligence” paradigm to enable differentiated service innovations and empower intelligent transformation of vertical industries. However, due to issues of data security, user privacy, wireless network transmission capability and etc

hidebound

Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/162251.jpg

相互影響

Introductory Methods for eQTL Analysesset. Results show that, 5 different oversampling method and SmoteTomek method can rebalance the dataset effectively, which can improve the recognition rate of models on the minority class obviously, while undersampling methods decrease the overall accuracy of models on imbalanced dataset. Meanwhile,