Deep Convolutional Neural Networks For Classification 99
Galaxy classification with deep convolutional neural networks
... Galaxy classification, using digital images captured from sky surveys to de- termine the galaxy morphological classes, is of great interest to astronomy ...images. Deep convolutional neural ...
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ImageNet Classification with Deep Convolutional Neural Networks
... 3.2 Training on Multiple GPUs A single GTX 580 GPU has only 3GB of memory, which limits the maximum size of the networks that can be trained on it. It turns out that 1.2 million training examples are enough to ...
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Classification of crystallization outcomes using deep convolutional neural networks
... 54]. Neural networks, including self-organizing maps, have also been 280 used classify these images [16, 55], with the most recent involving deep learning ...report classification rates for ...
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Rumor Classification Model Based on Deep Convolutional Neural Networks
... Convolutional Neural Network (CNN) is developed on the basis of the standard neural network, are as for neural network on the overall architecture is very similar, both by the neuron as a node ...
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Cystoscopy Image Classification Using Deep Convolutional Neural Networks
... well-known convolutional neural networks (CNNs) and a multilayer neural network was applied to classify bladder cystoscopy ...of neural networks is determining the learning rate ...
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Attributed Graph Classification via Deep Graph Convolutional Neural Networks
... social networks to biological networks, graphs are a natural way to represent a diverse set of real-world ...tional neural network with a pooling layer (AGCP for short), a novel end-to-end ...
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Utilization of Deep Convolutional Neural Networks for Remote Sensing Scenes Classification
... pre-trained deep CNN models and remote sensing datasets, the remote scene classification performances are shown in Table ...pre-trained deep CNNs are directly used as feature extractors in an ...
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String representations and distances in deep Convolutional Neural Networks for image classification
... So far, in the mentioned methods, image representation vectors capture the local properties of images, and an approximate global matching of these local features among images is actually computed for ...
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Improved Activation Functions of Deep Convolutional Neural Networks for Image Classification
... The CIFAR-10 dataset [5] is composed of 10 classes of natural images with 50,000 training image set and 10,000 testing image set. Each class have the same number of training and test images (5000, 1000). Each image has ...
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Fine-grained classification via mixture of deep convolutional neural networks
... novel deep convolutional neural network (DCNN) system for fine-grained image classification, called a mixture of DCNNs ...age classification problem is characterised by large intra- ...
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Classification of Malaria-Infected Cells Using Deep Convolutional Neural Networks
... 1.3. Classification of malaria-infected red blood cells using deep learning There has recently been an increasing amount of studies devoted to the application of computer vision and machine learning ...
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Resiliency in Deep Convolutional Neural Networks
... Figure 4.10 Performance recovery by retraining (self-healing) after weights are dropped throughout the AlexNet, VGG16, ResNet network. Fig. 4.11 shows that retraining improves in the next three architecture, out of which ...
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Deep convolutional neural networks capabilities for
... for the detection of MCs based on the use of deep convolutional neural networks (DCNNs).. We.[r] ...
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Deep Neural Language Model for Text Classification Based on Convolutional and Recurrent Neural Networks
... 6 single layer [44]. We were also inspired by the successful work proposed in [17], where a single layer of CNN was applied for sentence classification. It turns out that providing the network with good ...
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Convolutional Neural Networks for Accent Classification
... tional neural network architectures was implemented and it is proposed in this thesis in order to classify and accomplish as accurately as possible the accent recognition of a ...
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Convolutional Neural Networks for Sentence Classification
... In the present work, we train a simple CNN with one layer of convolution on top of word vectors obtained from an unsupervised neural language model. These vectors were trained by Mikolov et al. (2013) on 100 ...
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Convolutional neural networks for malware classification
... MALWARE CLASSIFICATION CHALLENGE 4.2 Microsoft Malware Classification Challenge In 2015, Microsoft hosted a competition in Kaggle with the goal of classifying malware into their respective families based on ...
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Classification of WBC for Blood Cancer Diagnosis using Deep Convolutional Neural Networks
... Abstract- Classification of Leukocytes (WBCs) is widely used in the medical field for the diagnosis of various blood cancers such as Leukemia, Myeloma ...Using Deep CNN we extracted minor intricacies in the ...
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Rate-Accuracy Trade-Off In Video Classification With Deep Convolutional Neural Networks
... Video Classification With Deep Convolutional Neural Networks Mohammad Jubran, Alhabib Abbas, Aaron Chadha and Yiannis Andreopoulos, Senior Member, IEEE Abstract—Advanced video ...
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Classification-Based Singing Melody Extraction Using Deep Convolutional Neural Networks
... Using Deep Convolutional Neural Networks Sangeun Kum 1 ID and Juhan Nam 1, * ID 1 Music and Audio Computing Lab, Korea Advanced Institute of Science and Technology, 291 Daehak-ro Yuseong-gu ...
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