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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Graph-based deep learning method for human-object interaction recognition / by Zhang, Jiali, 1987-, author 655167, Zuriahati Mohd. Yunos, 1977-, supervisor 605156, Fakulti Komputeran 538688

Scene text recognition by Muhammad Afiq Osman

“…Scene text recognition problem has recently seen interest within the deep learning community. …”
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Dataset issues in object recognition by Ponce, J, Berg, TL, Everingham, M, Forsyth, DA, Hebert, M, Lazebnik, S, Marszalek, M, Schmid, C, Russell, BC, Torralba, A, Williams, CKI, Zhang, J, Zisserman, A

“…Appropriate datasets are required at all stages of object recognition research, including learning visual models of object and scene categories, detecting and localizing instances of these models in images, and evaluating the performance of recognition algorithms. …”

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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Canonical frames for planar object recognition by Rothwell, CA, Zisserman, A, Forsyth, DA, Mundy, JL

“…Recognition is of partially occluded objects in cluttered scenes. …”

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. …”

Hybrid SLAM and object recognition on an embedded platform by Low, Timothy Zhi Hao

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Object recognition using deep learning features by Zhu, Daiqing

“…Many algorithms are available for automatic recognition of many different object categories. However, previous algorithms need to train classifier to rank proposal and learn from object class recognition datasets. …”
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3D object recognition using invariance by Zisserman, A, Forsyth, D, Mundy, J, Rothwell, C, Liu, J, Pillow, N

“…<p>The systems and concepts described in this paper document the evolution of the geometric invariance approach to object recognition over the last five years. Invariance overcomes one of the fundamental difficulties in recognising objects from images: that the appearance of an object depends on viewpoint. …”

ViObject: Harness Passive Vibrations for Daily Object Recognition with Commodity Smartwatches by Chen, Wenqiang, Lin, Shupei, Peng, Zhencan, Parizi, Farshid Salemi, Heo, Seongkook, Patel, Shwetak, Matusik, Wojciech, Zhao, Wei, Stankovic, John

“…This paper presents a novel system, ViObject, for passive object recognition that uses accelerometer and gyroscope sensor data from commodity smartwatches to identify untagged everyday objects. …”
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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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Video Google: a text retrieval approach to object matching in videos by Sivic, J, Zisserman, A

“…The object is represented by a set of viewpoint invariant region descriptors so that recognition can proceed successfully despite changes in viewpoint, illumination and partial occlusion. …”

Extreme learning machine based fast object recognition by Xu, Jiantao, Zhou, Hongming, Huang, Guang-Bin

“…This paper further studies the performance of ELM and its variants in object recognition using two different feature extraction methods. …”
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Small object recognition using machine learning techniques by Loy, Hui Juan

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Object recognition and pose estimation in robotic grasping system by Zhou, Jiadong

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Object class recognition by unsupervised scale-invariant learning by Fergus, R, Perona, P, Zisserman, A

“…Objects are modeled as flexible constellations of parts. …”