News article named entity recognition and analytics by Goh, Nicholas

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Keyword and named entity recognition on emergency call texts by Hu, Wanyu

“…This report utilize one of the methods of Artificial Intelligence (AI), specifically the Named Entity Recognition (NER) technique on Emergency Call Texts. …”
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Human action recognitions in video by Vu, Truong Thinh.

“…In some recent years, local space-time features technique has become an popular method for human action recognition. Many studies have been carried out, with many different types of detectors/descriptors proposed which gave promising result on traditional RGB videos. …”
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Keyword and named entity recognition on air traffic control text by Tay, Nikole Qiwei

“…This report will discuss the application of Named Entity Recognition (NER), a Natural Language Processing (NLP) method on Air Traffic Control (ATC) conversations to improve and attain higher precision in the communication between pilots and air traffic controllers. …”
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Generalized AutoNLP model for name entity recognition task by Wong, Yung Shen

“…Experiments are conducted to study the performance of our proposed architecture with BERT word embeddings on AutoNLP name entity recognition tasks.…”
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Deep learning-based text augmentation for named entity recognition by Surana, Tanmay

“…This thesis is focused on the development of an effective text augmentation method for Named Entity Recognition (NER) in the low-resource setting. …”
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Deep learning based action recognition by Ong, Zong You

“…Recently, the Graph Convolutional Network (GCN) has become a popular topic, and graph-based skeleton action recognition significantly improved in performance, because GCN can learn the neighbourhood information and body joints’ interaction in a directed way. …”
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Keyword and named entity recognition on air traffic control (ATC) data by Thia, Jeremy Ming Xuan

“…This project will explore several NLP tasks to perform named entity recognition on Air Traffic Control data, to be specific Air Traffic conversations. …”
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Human action recognition using machine learning by Cao, QingTian

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Multi-view human action recognition in meeting scenarios by Yin, Haixiang

“…Existing human action recognition systems tend to face the problem of human-to-human or human-to-object occlusion in some cases. …”
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A Ulam's game for video based action recognition by Zheng, Haofeng

“…In this dissertation, we propose a conditional early exiting framework with Ulam’s Game for action recognition. Since the action recognition system has extremely high requirements on dynamic performance, our system pays more attention to improving the detection efficiency of the system, hoping to obtain the detection results in a shorter time. …”
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Multiple human action recognition from video streams by Koh, Khai Huat

“…An important aspect of this research is to understand how a person would act in a given scenario. Human action recognition forms an integral part of such analysis. …”
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Effect of contextual information in human action recognition in videos by Koh, Hong Wei

“…With the growing threat of terrorism around the world, many law enforcement agencies have adopted computer vision technique to improve their operation efficiency. Human action recognition has been in the spotlight for the past few years due to its wide variety of capabilities such as gestures-based and surveillance applications. …”
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Action recognition using machine learning techniques for robots by Yue, Zhongqi

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Skeleton-based human action recognition with graph neural networks by U S Vaitesswar

“…Skeleton-based action recognition is a long-standing task in computer vision which aims to distinguish different human actions by identifying their unique characteristic patterns in the input data. …”
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Human action recognition using pose-based discriminant embedding by Saghafi, Behrouz, Rajan, Deepu

“…Thus they may be efficient in the frame recognition framework, but they will not guarantee to give optimum results when sequences are to be classified as in the case of action recognition in which temporal constraints convey important information. …”
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Active learning for ontological event extraction incorporating named entity recognition and unknown word handling by Han, Xu, Kim, Jung-jae, Kwoh, Chee Keong

“…Previous works of active learning, however, focused on the tasks of entity recognition and protein-protein interactions, but not on event extraction tasks for multiple event types. …”
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Visual event recognition in videos by learning from web data by Duan, Lixin, Xu, Dong, Tsang, Ivor Wai-Hung, Luo, Jiebo

“…We propose a visual event recognition framework for consumer videos by leveraging a large amount of loosely labeled web videos (e.g., from YouTube). …”
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Semi-CNN architecture for effective spatio-temporal learning in action recognition by Leong, Mei Chee, Prasad, Dilip K., Lee, Yong Tsui, Lin, Feng

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Robust and efficient deep learning methods for vision-based action recognition by Xu, Yuecong

“…Vision-based action recognition, which performs action recognition based solely on RGB frames, has received strong research interest thanks to its wide applications in various fields, e.g. surveillance, smart homes, and autonomous driving. …”
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