Titlebook: Intelligent Computing Theories and Application; 14th International C De-Shuang Huang,Kang-Hyun Jo,Xiao-Long Zhang Conference proceedings 20

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疏远天际

Fault Diagnosis and Control of a KYB MMP4 Electro-Hydraulic Actuator for LDVT Sensor Fault,cting and isolating the sensor fault signal is designed using the unknown input observer (UIO). In the sensor fault case, the fault detection and isolation (FDI) generates the feedback signal to the PID controller to drive the position of the actuator. The simulation and experimentations are performed to verify the performance of the FTC.

重力

载货清单

接合

An Enhanced HAL-Based Pseudo Relevance Feedback Model in Clinical Decision Support Retrieval,en, we propose three normalization methods to incorporate proximity information. Experimental results on 2016 TREC Clinical Support Medicine collections show that our proposed models are effective and generally superior to the state-of-the-art relevance feedback models.

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Credence

A Deep Reinforcement Learning Method for Self-driving,ributions, the sparse rewards is divided into three groups. The experience information for different rewards is fully utilized and the local optimum problem in the network training process is avoided. By comparing with the traditional method, simulation results show that the proposed method significantly reduces the training time of network.

注视

A Mask R-CNN Model with Improved Region Proposal Network for Medical Ultrasound Image,he further segmentation. Therefore, this paper improves the selection criteria of the anchor in the RPN layer, making the improved RPN layer more suitable for image segmentation tasks. Finally, the experimental results show that the improved model can achieve higher segmentation accuracy with the appropriate parameters selected.

CHURL

Breast Cancer Medical Image Analysis Based on Transfer Learning Model,nal layers and one max pooling layer before final fully connected layer. The experimental results have shown that this strategy is suitable for the problem in this paper. The paper indicates that the transfer learning model is an effective method with small-scale data, and it can be combined with deep learning algorithms.