Titlebook: Neural Information Processing; 26th International C Tom Gedeon,Kok Wai Wong,Minho Lee Conference proceedings 2019 Springer Nature Switzerla

LASH

Hierarchical Attention CNN and Entity-Aware for Relation Extractionh cannot preserve the position information and deal with the long sentences. In addition, the critical information for relation classification tends to present in a certain segment. A better method to extract feature in segment level is needed. In this paper, we propose a novel model with hierarchic

NUDGE

fibroblast

Group Loss: An Efficient Strategy for Salient Object Detectioncross entropy loss to optimize the networks for its capability in probability prediction. The function of cross entropy loss in salient object detection can be seemed as a pixel-wise label classification for images, which automatically predict whether the pixel is salient or non-salient. However, cr

植物茂盛

Trigger-Point

Multi-task Temporal Convolutional Network for Predicting Water Quality Sensor Datauality prediction, most studies focus on predicting a single water quality variable. When multiple water quality variables need to be estimated, preparing several data-driven models may require unaffordable computing resources. Also, the changing patterns of several water quality variables can only

大溝

CNN-LSTM Neural Networks for Anomalous Database Intrusion Detection in RBAC-Administered Modeles and access control techniques for database security, but they are not sufficient for detecting insider attacks. In order to detect threats for the database application, it is necessary to adopt role-based access control (RBAC) and classify the roles according to the authority of each user. In thi

Vulnerary

MC-HDCNN: Computing the Stereo Matching Cost with a Hybrid Dilated Convolutional Neural NetworkN, which is based on hybrid dilated convolution neural network, for computing matching cost of two image patches. HDCNN uses the dilated convolution of the series to obtain a larger receptive field, while avoiding the “gridding” effect and ensuring the integrity of the receptive field. In addition,

Petechiae

Convolutional Neural Network to Detect Thorax Diseases from Multi-view Chest X-Rayshreatening diseases. Not only certified radiologists are hard to find, stress, fatigue and experience contribute to the quality of an examination. It is ideal that a chest X-ray can be interpreted by an automated deep learning algorithm. In this paper, we proposed a stage-wise model that is founded

committed

and physical processes. The starting point of the text is the process - and not soil classification. Effects of weathering and new formation of minerals, mobilisation, transport, and breakdown or immobilisation of dissolved and suspended compounds are discussed. Soil processes and profiles are disc

Ambiguous

and physical processes. The starting point of the text is the process - and not soil classification. Effects of weathering and new formation of minerals, mobilisation, transport, and breakdown or immobilisation of dissolved and suspended compounds are discussed. Soil processes and profiles are disc