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

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Designing a spiking neural network system for object recognition by Thong, Jing Yuan

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Object matching and recognition under semi-affine transformation and occlusion by Thio, Hwee Li.

“…In this thesis, a method is proposed to extract features from an object for matching and recognition under simple transformations and occlusion. …”
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Face/object recognition and tracking on IoT device with 3D camera by Lin, Yuxin

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A sparse object category model for efficient learning and complete recognition by Fergus, R, Perona, P, Zisserman, A

“…<p>We present a &ldquo;parts and structure&rdquo; model for object category recognition that can be learnt efficiently and in a weakly-supervised manner: the model is learnt from example images containing category instances, without requiring segmentation from background clutter.…”

A sparse object category model for efficient learning and exhaustive recognition by Fergus, R, Perona, P, Zisserman, A

“…We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a semi-supervised manner: the model is learnt from example images containing category instances, without requiring segmentation from background clutter. …”

Generic Object Recognition with Local Receptive Fields Based Extreme Learning Machine by Bai, Zuo, Kasun, Liyanaarachchi Lekamalage Chamara, Huang, Guang-Bin

Subjects: “…Generic object recognition; local receptive fields; Extreme Learning Machine (ELM)…”
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MAS.622 / 1.126J Pattern Recognition & Analysis, Fall 2000 by Massachusetts Institute of Technology. Media Laboratory.

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Development of a machine-learning based object recognition system for quadrotors in urban environments by Lim, Brandon Yi Ming

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A hybrid approach towards the segmentation of range images for 3-D object recognition by Lim, Alan Wui Tze.

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Leveraging transfer learning for spatio-temporal human activity recognition from video sequences by Muneer Butt, Umair, Aman Ullah, Hadiqa, Letchmunan, Sukumar, Tariq, Iqra, Hafinaz Hassan, Fadratul, Wei Koh, Tieng

“…Moreover, the transfer learning paradigm is adopted to extract varied and fixed frames while reusing object identification information. Six state-of-the-art pre-trained models are exploited to find the best model for spatial feature extraction. …”
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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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Evaluation of different techniques for foreground object classification under illumination changes by Nguyen, Hang Nga

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

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Keyword and named entity recognition on air traffic control (ATC) data by Thia, Jeremy Ming Xuan

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Face recognition II by Mok, Valerie Hui Fang

“…In this final report, its objective is to examine and study the Open Computer Vision (OpenCV) techniques such as PCA using Visual Studio C# programming language and develop a simple Graphic User Interface (GUI) that assures system perform reliably with an input camera to perform live face detection and recognition. …”
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Efficient visual search of videos cast as text retrieval 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. …”