From an image to a text description of an image
This project presents an implementation of a search feature that allows user to look for a particular object of interest in a video. The main idea is to train a very deep neural network architecture that outputs a sequence of words that describe an image. The network consists of a convolutional neur...
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| Format: | Final Year Project |
| Language: | English |
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2017
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| Online Access: | http://hdl.handle.net/10356/70223 |
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| Institution: | Nanyang Technological University |
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sg-ntu-dr.10356-702232023-03-03T20:27:54Z From an image to a text description of an image Peter Chng Eng Siong School of Computer Science and Engineering DRNTU::Engineering::Computer science and engineering This project presents an implementation of a search feature that allows user to look for a particular object of interest in a video. The main idea is to train a very deep neural network architecture that outputs a sequence of words that describe an image. The network consists of a convolutional neural network (CNN) that learns features found on an image, and a long short-term memory (LSTM) unit that predicts the sequence of words from learnt features of the image. This project is not about real-time object detection, instead a video has to be preprocessed before a user may search for an object found visually inside the video. Bachelor of Engineering (Computer Science) 2017-04-17T07:22:49Z 2017-04-17T07:22:49Z 2017 Final Year Project (FYP) http://hdl.handle.net/10356/70223 en Nanyang Technological University 59 p. application/pdf |
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Asia |
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Singapore Singapore |
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English |
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DRNTU::Engineering::Computer science and engineering |
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DRNTU::Engineering::Computer science and engineering Peter From an image to a text description of an image |
| description |
This project presents an implementation of a search feature that allows user to look for a particular object of interest in a video. The main idea is to train a very deep neural network architecture that outputs a sequence of words that describe an image. The network consists of a convolutional neural network (CNN) that learns features found on an image, and a long short-term memory (LSTM) unit that predicts the sequence of words from learnt features of the image. This project is not about real-time object detection, instead a video has to be preprocessed before a user may search for an object found visually inside the video. |
| author2 |
Chng Eng Siong |
| author_facet |
Chng Eng Siong Peter |
| format |
Final Year Project |
| author |
Peter |
| author_sort |
Peter |
| title |
From an image to a text description of an image |
| title_short |
From an image to a text description of an image |
| title_full |
From an image to a text description of an image |
| title_fullStr |
From an image to a text description of an image |
| title_full_unstemmed |
From an image to a text description of an image |
| title_sort |
from an image to a text description of an image |
| publishDate |
2017 |
| url |
http://hdl.handle.net/10356/70223 |
| _version_ |
1759858272626540544 |