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Segmentation of dermoscopy images based on fully convolutional neural network
2017 IEEE International Conference on Image Processing (ICIP), 2017Lesion segmentation is one of the crucial steps for computerized dermoscopy image analysis. To accurately extract lesion borders from dermoscopy images, a novel segmentation method based on fully convolutional neural network is proposed in this paper.
Zilin Deng +4 more
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Carpal Bone Segmentation Using Fully Convolutional Neural Network
Current Medical Imaging Formerly Current Medical Imaging Reviews, 2019Background: Bone Age Assessment (BAA) refers to a clinical procedure that aims to identify a discrepancy between biological and chronological age of an individual by assessing the bone age growth. Currently, there are two main methods of executing BAA which are known as Greulich-Pyle and Tanner-Whitehouse techniques.
Liang Kim Meng +7 more
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Fully Residual Convolutional Neural Networks for Aerial Image Segmentation
Proceedings of the Ninth International Symposium on Information and Communication Technology - SoICT 2018, 2018Semantic segmentation from aerial imagery is one of the most essential tasks in the field of remote sensing with various potential applications ranging from map creation to intelligence service. One of the most challenging factors of these tasks is the very heterogeneous appearance of artificial objects like buildings, cars and natural entities such as
Dinh Viet Sang, Nguyen Duc Minh
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Gait Recognition by Combining Recurrent Neural Network and Fully Convolutional Network
International Journal of Pattern Recognition and Artificial IntelligenceGait recognition is one of the key technologies for exoskeleton robot control. The existing gait recognition methods cannot meet the needs of real-time control well in terms of recognition accuracy and robustness. In this paper, a gait recognition method based on the recurrent neural network and fully convolutional network (RNN-FCN) algorithm is ...
Xinbin Zhang +4 more
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Intelligent character recognition using fully convolutional neural networks
Pattern Recognition, 2019Abstract The recognition of handwritten text is challenging as there are virtually infinite ways a human can write the same message. Deep learning approaches for handwriting analysis have recently demonstrated breakthrough performance using both lexicon-based architectures and recurrent neural networks.
Raymond W. Ptucha +5 more
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On the Potential of Fully Convolutional Neural Networks for Musical Symbol Detection
2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), 2017Musical symbol detection on the page is an outstanding Optical Music Recognition (OMR) subproblem. We propose using a fully convolutional segmentation network to produce high-quality pixel-wise symbol probability masks. Experiments on notehead detection show a very promising detection f-score of 0.98 with elementary detection methods.
Matthias Dorfer +2 more
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Infrared Small Target Detection Based on a Temporally-Aware Fully Convolutional Neural Network
Remote Sensing, 2023Peng Han, Zhengrong Zuo
exaly
Enhanced Millimeter-Wave 3-D Imaging via Complex-Valued Fully Convolutional Neural Network
Electronics (Switzerland), 2022Houjun Sun, Shiyong Li, Ke Miao
exaly
Fully Convolutional Neural Network for Event Camera Pose Estimation
Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 2023Ahmed Tabia +2 more
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