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PAGE-Net: Interpretable and Integrative Deep Learning for Survival . . . We propose a biologically interpretable deep learning model (PAGE-Net) that integrates histopathological images and genomic data, not only to improve survival prediction, but also to identify genetic and histopathological patterns that cause different survival rates in patients
PAGE-Net - GitHub PAGE-Net =========================================================================== W Wang, S Zhao, J Shen, S C H Hoi, and A Borji, Salient Object Detection with Pyramid Attention and Salient Edges, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019
PageNet - Wikipedia Based in Dallas, PageNet held the distinction of building and operating the most extensive one-way paging network in the United States, growing to more than 90 offices across the United States The company extended operations to Canada and Brazil
PageNet: Towards End-to-End Weakly Supervised Page-Level . . . - Springer Although some approaches aimed at page-level text recognition have been proposed in recent years, they either are limited to simple layouts or require very detailed annotations including expensive line-level and even character-level bounding boxes To this end, we propose PageNet for end-to-end weakly supervised page-level HCTR
[PDF] PageNet: Towards End-to-End Weakly Supervised Page-Level . . . To this end, we propose PageNet for end-to-end weakly supervised page-level HCTR PageNet detects and recognizes characters and predicts the reading order between them, which is more robust and flexible when dealing with complex layouts including multi-directional and curved text lines
PageNet | Proceedings of the 4th International Workshop on Historical . . . In this work, we present a deep learning system, PageNet, which identifies the main page region in an image in order to segment content from both textual and non-textual border noise In PageNet, a Fully Convolutional Network obtains a pixel-wise segmentation which is post-processed into a quadrilateral region
顶刊IJCV 2022！PageNet：面向端到端弱监督篇幅级手写中文文本识别-CSDN博客 本文简要介绍2022年8月发表于IJCV的论文“PageNet: Towards End-to-End Weakly Supervised Page-Level Handwritten Chinese Text Recognition”的主要工作。 该工作针对篇幅级手写中文文本识别问题，提出了端到端弱监督的方法PageNet。