17 March 2017 Very deep recurrent convolutional neural network for object recognition
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Proceedings Volume 10341, Ninth International Conference on Machine Vision (ICMV 2016); 1034107 (2017) https://doi.org/10.1117/12.2268672
Event: Ninth International Conference on Machine Vision, 2016, Nice, France
Abstract
In recent years, Computer vision has become a very active field. This field includes methods for processing, analyzing, and understanding images. The most challenging problems in computer vision are image classification and object recognition. This paper presents a new approach for object recognition task. This approach exploits the success of the Very Deep Convolutional Neural Network for object recognition. In fact, it improves the convolutional layers by adding recurrent connections. This proposed approach was evaluated on two object recognition benchmarks: Pascal VOC 2007 and CIFAR-10. The experimental results prove the efficiency of our method in comparison with the state of the art methods.
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Sourour Brahimi, Sourour Brahimi, Najib Ben Aoun, Najib Ben Aoun, Chokri Ben Amar, Chokri Ben Amar, } "Very deep recurrent convolutional neural network for object recognition", Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 1034107 (17 March 2017); doi: 10.1117/12.2268672; https://doi.org/10.1117/12.2268672
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