摘要 This paper addresses the problem of estimating the depth map of a scene given a single RGB image. We propose a fully convolutional architecture, encompassing residual learning, to model the ambiguous mapping between monocular images and depth maps. In order to improve the output resolution, w...
Chang PD: Fully Convolutional Deep Residual Neural Networks for Brain Tumor Segmentation. In: Crimi A, Menze B, Maier O, Reyes M, Winzeck S, Handels H, editors. Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries: Second International Workshop, BrainLes 2016, with ...
Enlarging the spatial resolution of features generated by fully convolutional networks (FCNs) can improve the performance of semantic segmentation. To achieve this goal, deeper network with deconvolutional structure can be applied. However, when the network architecture becomes more complex, the training ...
论文: FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics 论文地址:https://arxiv.org/pdf/1612.05360 论文思想: FusionNet利用机器学习的最新进展,如语义分割(U-Net)和残差神经网络,新引入了基于累加的跳过连接,允许更深入的网络体系结构来实现更精确的分割。 论文...
We propose a novel deep network structure called "Network In Network" (NIN) to enhance model discriminability for local patches within the receptive field. The conventional convolutional layer uses linear filters followed by a nonlinear ... M Lin,Q Chen,S Yan - 《Computer Science》 被引量: 21...
S. Hong, J. Oh, H. Lee, and B. Han. Learning transferrable knowledge for semantic segmentation with deep convolutional neural network. In CVPR, 2016. The research of this topic has proceeded along three different dimensions: unsupervised adaptation, supervised adaptation and semi-supervised adaptati...
Fully convolutional multi-scale residual DenseNets for cardiac segmentation and automated cardiac diagnosis using ensemble of classifiers Kollerathu, and G. Krishnamurthi, "Fully convolutional multi-scale residual DenseNets for cardiac segmentation and automated cardiac diagnosis using en- ... M Khened,...
Fully Convolutional Neural Network: A solution to infer animal behaviours from multi-sensor data In this study, we adapt a fully convolutional neural network that was originally developed for biomedical 3D image segmentation: the V-net. We test it ... SCD Jeantet - 《Ecological Modelling》 被引...
The depth predictions for this specific image (top right corner) were obtained with a pre-trained fully convolutional residual network (FCRN)11. Full size image The protein inter-residue distance prediction problem is to predict a pair-wise distance matrix (2D) from a protein sequence (one-...
FLGCNN: A novel fully convolutional neural network for end-to-end monaural speech enhancement with utterance-based objective functions[J]. Applied Acoustics, 2020, 170: 107511. 摘要 提出了一种新的全卷积神经网络(FCN),称为FLGCNN,用于解决时域端到端语音增强问题。提出的FLGCNN主要建立在编码器和译码...