[PDF] Top 20 ImageNet Classification with Deep Convolutional Neural Networks
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ImageNet Classification with Deep Convolutional Neural Networks
... big neural networks that already take several days to ...the neural network samples a different architecture, but all these architectures share ... See full document
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Experimental Evaluation
... ImageNet Classification with Deep Convolutional Neural Networks Do CIFAR-10 classifiers generalize to CIFAR-10?. – We will provide a list of ~10 papers.[r] ... See full document
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Convolutional Neural Networks for Sentence Classification
... with deep learning meth- ods has involved learning word vector representa- tions through neural language models (Bengio et ...for classification (Collobert et ... See full document
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Ensemble of Deep Convolutional Neural Networks for Classification of Early Barrett's Neoplasia Using Volumetric Laser Endomicroscopy
... 2) our dataset is larger than the other two references (Scheeve et al. compares only 18 patients). Our work improves in both the data acquistion and the evaluation method, by using a dataset of 22 in-vivo patients to ... See full document
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Classification-Based Singing Melody Extraction Using Deep Convolutional Neural Networks
... Classification-Based Singing Melody Extraction Using Deep Convolutional Neural Networks1. Sangeun Kum 1 ID and Juhan Nam 1, * ID.[r] ... See full document
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Phone recognition with hierarchical convolutional deep maxout networks
... Deep convolutional neural networks (CNNs) have recently been shown to outperform fully connected deep neural networks (DNNs) both on low-resource and on large-scale speech ... See full document
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A general purpose intelligent surveillance system for mobile devices using deep learning
... The classification module is based on a neural network using Deep Learning ...the convolutional neural network is presented and analyzed in the context of the four selected ... See full document
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Resiliency in Deep Convolutional Neural Networks
... Fig. 4.11 shows that retraining improves in the next three architecture, out of which YOLO performs remarkably well compared to GoogleNet and SqueezeNet up until 60% of the weights have been corrupted. This is because of ... See full document
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Research on Classification of Surface Defects of Hot rolled Steel Strip Based on Deep Learning
... Convolution layer is a layer in which the input data is extracted for feature extraction. By convolution, a set of images can be generated for subsequent use. The pooling layer is mainly used to reduce the size of the ... See full document
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Analysis of Pre Trained Convolutional Neural Networks to Build a Flower Classification System
... three convolutional neural networks, pre-trained on the ImageNet dataset, on the basis of accuracy measure obtained by training each model on a custom dataset, generated by using web scraping ... See full document
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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 ...volutional neural networks (CNN), which operate directly on weighted, attributed ... See full document
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Deep Convolutional Neural Networks Capabilities for Binary Classification of Polar Mesocyclones in Satellite Mosaics
... for the detection of MCs based on the use of deep convolutional neural networks (DCNNs).. As a 21.[r] ... See full document
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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] ... See full document
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Classification of CITES-listed and other neotropical Meliaceae wood images using convolutional neural networks
... a deep convolution neural network, trained using transfer learning, capable of separating anatomically similar commercial and endangered woods of the Meliaceae family at both the genus and species level, ... See full document
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Understanding Convolutional Neural Networks for Text Classification
... We note that empirically and intuitively, the more filters we utilize in the network, the less correlation there is between each filter’s class and the final classification, as the decision is being made by a ... See full document
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Relation Classification via Convolutional Deep Neural Network
... As mentioned in section 3.2, all of the tokens are represented as word vectors, which have been demon- strated to correlate well with human judgments of word similarity. Despite their success, single word vector models ... See full document
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Liu_unc_0153D_16675.pdf
... using deep neural ...separate deep neural net- ...two neural networks with a dependency between ...shared convolutional layers and predic- tion layers for these two ... See full document
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Deep Learning Pre-Trained Architecture Of Alex Net And Googlenet For DICOM Image Classification
... image classification is very important for diagnose and treatment purpose which is used to classify the historical medical images from the huge amount of data ...image classification architecture to ... See full document
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Fast image recognition of transmission tower based on big data
... region-based convolutional neural networks (Rcnn) convolutional architecture for fast feature embedding (Caffe) to get deep learning of the massive transmission tower image, extract the ... See full document
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Deep learning for smart agriculture: Concepts, tools, applications, and opportunities
... supports deep learning algorithms, including CNN, RNN, GAN and other variants, which can be used on Linux, Windows, and Mac ...of deep learning application programming interfaces (API) including basic ... See full document
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