Exam proctoring is a hectic task i.e., the monitoring of students’ activities becomes difficult for supervisors in the examination rooms.It is a costly approach that requires much labor.Also, it is a difficult task for supervisors to keep an eye on all students at a time.Automatic exam activities recognition is therefore necessitating and a
Prediction of futile recanalisation after endovascular treatment in acute ischaemic stroke: development and validation of a hybrid machine learning model
Background Identification of futile recanalisation following endovascular therapy (EVT) in patients with acute ischaemic stroke is both crucial and challenging.Here, we present Table Lamp a novel risk stratification system based on hybrid machine learning method for predicting futile recanalisation.Methods Hybrid machine learning models were develo
A Scale Aggregation and Spatial-Aware Network for Multi-View Crowd Counting
Previous multi-view crowd counting methods underperform in maintaining scale consistency across views and overlook the negative effect of the complex background.To solve these problems, a scale aggregation and spatial-aware network for multi-view crowd counting (SASNet) is proposed.Firstly, we design a multi-branch adaptive scale aggregation module
A Named Entity Recognition Method Based on Knowledge Distillation and Efficient GlobalPointer for Chinese Medical Texts
The task of named entity recognition has been widely used in medical text analysis, but there is still the problem of poor transfer ability in practical applications.This work proposes a novel named entity recognition method based on a proposed knowledge distillation framework and Efficient GlobalPointer for Chinese biomedical and clinical data.Spe