Fully-parallel Convolutional Neural Network Hardware
CoRR, 2020 8 pages, 6 figures, to be submitted to an IEEE ...
Christiam F. Frasser +5 more
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Fully Convolutional Neural Networks for Newspaper Article Segmentation [PDF]
2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), 2017 Segmenting newspaper pages into articles that semantically belong together is a necessary prerequisite for article-based information retrieval on print media collections like e.g. archives and libraries. It is challenging due to vastly differing layouts of papers, various content types and different languages, but commercially very relevant for e.g ...
Benjamin Bruno Meier +4 more
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Binary and Multiclass Text Classification by Means of Separable Convolutional Neural Network
Inventions, 2021 In this paper, the structure of a separable convolutional neural network that consists of an embedding layer, separable convolutional layers, convolutional layer and global average pooling is represented for binary and multiclass text classifications ...
Elena Solovyeva, Ali Abdullah
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Equivalence of approximation by convolutional neural networks and fully-connected networks [PDF]
Proceedings of the American Mathematical Society, 2019 Convolutional neural networks are the most widely used type of neural networks in applications. In mathematical analysis, however, mostly fully-connected networks are studied. In this paper, we establish a connection between both network architectures.
Petersen, Philipp, Voigtlaender, Felix
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Fully Convolutional Neural Network with Relation Aware Context Information for Image Parsing
, 2021 Image parsing is among the core tasks in the field of computer vision. The automatic pixel-wise segmentation offers great potential in terms of application adaptability.
Azam, Basim +5 more
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Image Quality Predictor with Highly Efficient Fully Convolutional Neural Network
Advances in Multimedia, 2022 A highly efficient deep fully convolutional neural network (DFCN) for image quality assessment (IQA) is designed in this paper. The DFCN consists of two branches, one scoring local patches and the other estimating the weights of local patches to enhance ...
Cao Yu-Dong, Liao Xin-Lin, Liu Hai-Yan
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Convolutional neural network aided chemical species tomography for dynamic temperature imaging [PDF]
, 2022 Chemical Species Tomography (CST) using Tunable Diode Laser Absorption Spectroscopy (TDLAS) is an in-situ technique to reconstruct the two-dimensional temperature distributions in combustion diagnosis.
Lengden, Michael +5 more
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Fully convolutional neural networks for polyp segmentation in colonoscopy [PDF]
SPIE Proceedings, 2017 Colorectal cancer (CRC) is one of the most common and deadliest forms of cancer, accounting for nearly 10% of all forms of cancer in the world. Even though colonoscopy is considered the most effective method for screening and diagnosis, the success of the procedure is highly dependent on the operator skills and level of hand-eye coordination.
Patrick Brandao +9 more
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Fully automatic wound segmentation with deep convolutional neural networks [PDF]
Scientific Reports, 2020 AbstractAcute and chronic wounds have varying etiologies and are an economic burden to healthcare systems around the world. The advanced wound care market is expected to exceed $22 billion by 2024. Wound care professionals rely heavily on images and image documentation for proper diagnosis and treatment.
Chuanbo Wang +7 more
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Probabilistic Spatial Regression using a Deep Fully Convolutional Neural Network [PDF]
, 2017 Probabilistic predictions are often preferred in computer vision problems because they can provide a confidence of the predicted value. The recent dominant model for computer vision problems, the convolutional neural network, produces probabilistic ...
Knapp, K. +2 more
core +4 more sources