With the continuous growth of global submarine cable laying length, frequency faults and caused economic losses are increasing year by year. Rapid identification can reduce losses. For several typical faults, this paper proposes a recognition method based on FCN-GRU-SVM. First, pre-process original signal, then import data into FCN-GRU to extract signal features, finally use SVM identify fault ...

In this report, we investigate the synchronization of temporal activity in an electrically coupled neural network model. The electrical coupling is established by homotypic static gap-junctions (Connexin 43). Two distinct network topologies, namely: sparse random network, (SRN) and fully connected network, (FCN) are used to establish the connectivity. The strength of connectivity in the FCN is ...

This paper investigates how to rapidly and accurately localize facial landmarks in unconstrained, cluttered environments rather than in the well segmented face images. We present a novel Backbone-Branches Fully-Convolutional Neural Network (BB-FCN), which produces facial landmark response maps directly from raw images without relying on pre-process or sliding window approaches. BB-FCN contains ...

We present region-based, fully convolutional networks for accurate and efficient object detection. In contrast to previous region-based detectors such as Fast/Faster R-CNN [7, 19] that apply a costly per-region subnetwork hundreds of times, our region-based detector is fully convolutional with almost all computation shared on the entire image. To achieve this goal, we propose position-sensitive...

Accurate electricity consumption forecasting in the power grids ensures efficient generation and distribution of electricity. Keeping this mind, paper introduces a novel deep learning model, termed Gated-FCN, for short-term load forecasting. The key idea is to introduce an automated feature selection model includes eight-layered Fully Convolutional Network (FCN-8) which hand-crafted that requir...

I would like to thank authors Judy Shackelford, Diana Weyhenmeyer, and Linda Mabus (2014) for bringing attention to the important role faith community nurses (FCNs) play in preventive and screening services in communities that may be underserved or lack strong medical connections. As the authors discuss, individuals who live in rural communities may not readily access preventive care. Because F...

Fully Convolutional Neural Network (FCN) has been widely applied to salient object detection recently by virtue of high-level semantic feature extraction, but existing FCN-based methods still suffer from continuous striding and pooling operations leading loss spatial structure blurred edges. To maintain the clear edge objects, we propose a novel Edge-guided Non-local FCN (ENFNet) perform edge-g...

Jesús González-Rubio and Jesús Andrés-Ferrer and Germán Sanchis-Trilles Guillem Gascó and Pascual Martı́nez-Gómez and Martha-Alicia Rocha Joan-Andreu Sánchez and Francisco Casacuberta Instituto Tecnológico de Informática Departamento de Sistemas Informáticos y Computación Universidad Politécnica de Valencia {jegonzalez|jandres|gsanchis}@dsic.upv.es {ggasco|pmartinez|mrocha}@dsic.upv.es {jandreu|...