Scene text recognition by Muhammad Afiq Osman

“…Scene text recognition problem has recently seen interest within the deep learning community. …”
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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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Text recognition from images mobile application by Phua, Melvin

“…Recognizing text from images with computers has been made possible through the advancement of Computer Vision or a more specific term relevant to this project, OCR (Optical Character Recognition). …”
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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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Personality recognition from text based on the MBTI model by Chew, Andrel Kit Waye

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Deep structured output learning for unconstrained text recognition by Jaderberg, M, Simonyan, K, Vedaldi, A, Zisserman, A

“…The resulting model is a more accurate system on standard real-world text recognition benchmarks than character prediction alone, setting a benchmark for systems that have not been trained on a particular lexicon. …”

Keyword and named entity recognition on air traffic control text by Tay, Nikole Qiwei

“…A demo website which allows the input of ATC text features the working application of NER by returning the highlighted and annotated name entities.…”
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Training deep network models for accurate recognition of texts in scenes by Chen, Cheng

“…Scene Text Recognition is an important task because of its many potential applications in the industries. …”
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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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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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Training deep network models for accurate recognition of texts in scene images by Chen, Pengfei

“…Recognition of text automatically is playing an important role and act as a foundation in Artificial Intelligence field. …”
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Training deep network models for accurate recognition of texts in scene images by Zhang, Weilun

“…Text recognition from scene images constitutes still a very challenging task because of various backgrounds, variations in size and space, as well as irregular arrangements. …”
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Sound event recognition in unstructured environments using spectrogram image processing by Dennis, Jonathan William

“…The objective of this research is to develop feature extraction and classification techniques for the task of sound event recognition (SER) in unstructured environments. …”
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A size and position invariant event-based human posture recognition algorithm by Chen, Shoushun, Folowosele, Fopefolu, Kim, Dongsoo, Vogelstein, R. Jacob, Etienne-Cummings, Ralph, Culurciello, Eugenio

“…Combining bioinspired event-based image acquisition and hardware friendly feature extraction and classification algorithm will lead to a promising technology for use in wireless sensor network.…”
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Generalized AutoNLP model for name entity recognition task by Wong, Yung Shen

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Comparison of character recognition performance - bayes classifier and neural network methods by Low, Siew Eng.

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Algorithms for extracting text from degraded document images by Chen, Yan

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Robust text-independent speaker verification in environmental noise by Panda, Ashish

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Event detection in spatiotemporal soccer data using neural networks by Wilbert

“…This project implements and evaluates three-layer and four-layer artificial neural networks (ANN(3) and ANN(4)) as well as recurrent neural networks (RNNs) for automatic event detection in spatiotemporal soccer data. The datasets used were derived from the synthetic SoccER (Soccer Event Recognition) dataset, which was originally generated using modified open-source soccer simulation game engine. …”
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Compressed event sensing (CES) volumes for event cameras by Lin, Songnan, Ma, Ye, Chen, Jing, Wen, Bihan

“…Through synthetic phantom validation on dense frame regression and two downstream applications involving intensity-image reconstruction and object recognition tasks, we demonstrate the superior performance of CES volumes compared to state-of-the-art event representations.…”
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