Background: Words in the Mental Lexicon (ML) construct semantic field through associative and/ or semantic connections, with a pervasive native speaker preference for the former. Non-native preferences, however, demand further inquiry. Previous studies have revealed inconsistent Lexical Access (LA) patterns due to the limitations in the methodology and response categorization. Objectives: To f...

Automatic short answer grading (ASAG) is the automated process of assessing answers based on natural language using computation methods and machine learning algorithms. Development of large-scale smart education systems on one hand and the importance of assessment as a key factor in the learning process and its confronted challenges, on the other hand, have significantly increased the need for ...

Automatic short answer grading (ASAG) is the automated process of assessing answers based on natural language using computation methods and machine learning algorithms. Development of large-scale smart education systems on one hand and the importance of assessment as a key factor in the learning process and its confronted challenges, on the other hand, have significantly increased the need for ...

The significant amount of training data required for Convolutional Neural Networks has become a bottleneck applications like semantic segmentation. Few-shot segmentation algorithms address this problem, with an aim to achieve good performance in the low-data regime, few annotated images. Recent approaches based on class-prototypes computed from available have achieved immense success task. In w...