Study of object detection using region-based fully convolutional neural networks
With the fast pace of economic development, deep learning has become one of the fastest growing field in recent over ten years. It has been applied and implemented widely such as Intelligent Transportation System (ITS), industrial automation system, data statistic and robotic. Convolutional Neural N...
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sg-ntu-dr.10356-777692023-07-07T17:56:30Z Study of object detection using region-based fully convolutional neural networks Liang, Yuehui Lu Yilong School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering With the fast pace of economic development, deep learning has become one of the fastest growing field in recent over ten years. It has been applied and implemented widely such as Intelligent Transportation System (ITS), industrial automation system, data statistic and robotic. Convolutional Neural Network (CNN) is one of the most representative network structures in deep learning technology, and has achieved great success in the field of image processing. This paper covers the concept and development of one of the most popular object detection method-region based fully convolutional neural network (R-FCN). And use high-end computer to evaluate the performance of the model in different data set training and compare with the other convolutional neural network method. Bachelor of Engineering (Electrical and Electronic Engineering) 2019-06-06T04:47:33Z 2019-06-06T04:47:33Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/77769 en Nanyang Technological University 49 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering Liang, Yuehui Study of object detection using region-based fully convolutional neural networks |
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With the fast pace of economic development, deep learning has become one of the fastest growing field in recent over ten years. It has been applied and implemented widely such as Intelligent Transportation System (ITS), industrial automation system, data statistic and robotic. Convolutional Neural Network (CNN) is one of the most representative network structures in deep learning technology, and has achieved great success in the field of image processing. This paper covers the concept and development of one of the most popular object detection method-region based fully convolutional neural network (R-FCN). And use high-end computer to evaluate the performance of the model in different data set training and compare with the other convolutional neural network method. |
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Lu Yilong |
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Lu Yilong Liang, Yuehui |
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Final Year Project |
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Liang, Yuehui |
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Liang, Yuehui |
title |
Study of object detection using region-based fully convolutional neural networks |
title_short |
Study of object detection using region-based fully convolutional neural networks |
title_full |
Study of object detection using region-based fully convolutional neural networks |
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Study of object detection using region-based fully convolutional neural networks |
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Study of object detection using region-based fully convolutional neural networks |
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study of object detection using region-based fully convolutional neural networks |
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2019 |
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http://hdl.handle.net/10356/77769 |
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1772827956268236800 |