fully convolutional neural network (FCN)
Probabilistic Spatial Regression using a Deep Fully Convolutional Neural Network
... the convolutional neural network, produces probabilistic out- put for classification and segmentation ...novel fully convolutional neural network capable of producing a ...
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Beef Cattle Instance Segmentation Using Fully Convolutional Neural Network
... the most refined of FCN architectures (others being FCN-16s and FCN-32s) as a backbone network (feature and score map extractor). The output of FCN8s consists of two score maps (object and background score maps) ...
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Recurrent Fully Convolutional Networks Based on Optical Flow for Video Eyes Fixation Prediction
... process. Fully convolutional neural network (FCN) was currently widely used in image segmentation, target detection and so ...The fully convolutional neural network ...
5
Image Segmentation Using Convolutional Neural Network
... creating a training seed which consists of manually and semi manually segmented images. They took the help of a data set of images from Berea sandstone. They divided the dataset among groups of training, testing and ...
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Simple and Efficient Smoke Segmentation Based on Fully Convolutional Network
... a fully convolutional neural network for smoke segmentation of flare stack ...the network is more robust to background ...segmentation network, the proposed algorithm has an ...
5
A Novel Method for Remotely Sensed Hyperspectral Image Classification Based on Convolutional Neural Network
... feed-forward neural network which is a combination of convolution layer, pooling and FCN ...deep neural network architecture which learns spectral-spatial features and gives better performance ...
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Land Cover Maps Production with High Resolution Satellite Image Time Series and Convolutional Neural Networks: Adaptations and Limits for Operational Systems
... particular, convolutional neural networks learn features which take into account the context of the pixels and therefore a better representation of the data can be ...assess fully ...
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Fully automated, real-time 3D ultrasound segmentation to estimate first trimester placental volume using deep learning
... dependant. Fully automating the segmentation process would potentially allow the use of placental volume to screen for increased risk of pregnancy ...A fully convolutional neural ...
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Two-phase multi-model automatic brain tumour diagnosis system from magnetic resonance images using convolutional neural networks
... Artificial neural network; BPN: Back propagation neural network; BraTS: Brain tumour segmentation; CAD: Computer-aided diagnosis; CNN: Convolutional neural network; DNN: ...
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Convolutional Neural Network in Medical Diagnosis
... 16 Convolutional/Fully Connected layers and its uniform architecture makes it very ...the network is a critical component for good ...first fully connected layer, and can be removed with no ...
8
A Convolutional Neural Network for Modelling Sentences
... Various neural sentence models have been de- ...of Neural Bag-of-Words (NBoW) ...more fully connected ...Recursive Neural Network (RecNN) (Pollack, 1990; K¨uchler and Goller, 1996; ...
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Identification Of Weeds From Crops Using Convolutional Neural Network
... of Convolutional Neural Networks. The topology of the proposed Neural Network used was the CaffeNet network, which is a imitation of the already implemented topology in AlexNet ...
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Fixed layer Convolutional Neural Network
... Abstract— Fully trained convolutional neural networks are being used nowadays in various ...a network with fixed weights on the filters, how is its performance compared with a fully ...
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Scale Invariant Fully Convolutional Network: Detecting Hands Efficiently
... of convolutional neural networks (CNNs) in computer vision, many recent hand detection methods are proposed based on CNN ...the Fully Con- volutional Network (Long, Shelhamer, and Darrell ...
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Segmentation Guided Attention Networks for Visual Question Answering
... on Neural Networks, where a Convolutional Neural is first used to extract out image features and then these image features are used along with some RNN model to understand the question and generate ...
6
A CNN Based Approach for Garments Texture Design Classification
... convolution neural network; such as Convolution layer, Pooling layer and Fully-Connected (FC) ...five convolutional layers and three fully connected ...three fully connected ...
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Automatic Brain Tumor Segmentation by Deep Convolutional Networks and Graph Cuts
... traditional neural network layers, every output unit interacts with every input unit, as shown in Figure ...However, convolutional neural networks typically have sparse interac- tions between ...
96
A review of image-based automatic facial landmark identification techniques
... The accurate identification of landmarks within facial images is an important step in the completion of a number of higher-order computer vision tasks such as facial recognition and facial expression analysis. While ...
23
A Linguistically Informed Convolutional Neural Network
... powerful for unbounded dependencies, but tweets are short; the sentiment of a tweet is usually de- termined by one part of it and unlike RNN/LSTM, convolution plus max pooling can learn to focus on that. Recursive ...
6
A NOVEL TWO DIMENSIONAL SPECTRAL/SPATIAL HYBRID CODE FOR OPTICAL CODE DIVISION MULTIPLE ACCESS SYSTEM
... An ear recognition method is proposed by Revaud et al. [18], which uses the Scale-Invariant Features Transform (SIFT) method to detect features and create descriptors for them. These features are extracted for the model ...
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