[PDF] Top 20 DNA Sequence Classification by Convolutional Neural Network
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DNA Sequence Classification by Convolutional Neural Network
... The convolutional neural network also has been applied in text data problems such as topic categorization, spam detection, and sentiment ...the convolutional neural ...the ... See full document
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Cluster Gated Convolutional Neural Network for Short Text Classification
... text classification. Kim (2014) proposed a convolutional neural network (CNN) architecture that utilized multiple parallel convolutional layers with varying filter window sizes and ... See full document
10
Vehicle Classification with Convolutional Neural Network on Motion Blurred Images
... Various of vehicle classification methods have been proposed in the last few years [1, 2, 3, 4]. Petrovi and Cootes [5] classify vehicles into different classes by using the number plate to locate region of ... See full document
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Word Embeddings and Convolutional Neural Network for Arabic Sentiment Classification
... social network websites, forums, video sharing websites, blogs and e-commerce websites, leading to a most rising research fields caused by the important opinionated web ... See full document
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Deep machine learning provides state of the art performance in image based plant phenotyping
... performance. Neural networks re- quire non-linear functions between layers in order to capture the complex non-linearity of the classification ...each convolutional filter at each position is passed ... See full document
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Histopathological Biopsy Image Classification Based On Convolutional Neural Network
... CNN works on the 2-D images. The architecture of CNN is designed in the three layers. The three types of layers are: convolutional layer, subsampling layer and output layer. Each layer in the CNN acts as a filter ... See full document
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Multilingual Modal Sense Classification using a Convolutional Neural Network
... For can many filters recognise accomplish- ments which go along with dynamic sense, e.g. You can do it/make it to NY. Others detect words indicating possibility (ep), negation (de), discourse markers, animate subject (de ... See full document
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Comparison of Image Classification Techniques: Binary and Multiclass using Convolutional Neural Network and Support Vector Machines
... Convolutional networks are designed to reduce the dimensionality of images in a variety of ways [10], [11]. One way is Filter Stride while other way is down sampling. Next to convolution, max pooling, down ... See full document
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Disease Detection in the Leaves of Multiple Plants
... deep Convolutional Neural Network (CNN) technique is used for the detection and classification of different types of diseases effected to the plant ...CNN network is trained with 5 ... See full document
5
An Automated System for Identification of Skeletal Maturity using Convolutional Neural Networks Based Mechanism
... 4 convolutional layers where the layers have 5X5 sized 32 filters, 3X3 sized 64 filters, 3X3 sized 64 filters, 3X3 sized 32 filters ...radius classification results. We can observe that the ... See full document
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A Language Independent Neural Network for Event Detection
... recurrent neural network (RNN) (Mikolov et ...word. Convolutional neural network (CNN) (LeCun et ...hybrid neural network incorporating two types of neural ... See full document
6
Integrated Animal Recognition and Detection Using Deep Convolutional Neural Network
... Design a framework for animal recognition in the wild, aiming at a fully automatic wildlife spotting system. Our work is motivated by the state-of-the-art power of recent deep CNN models for image classification, ... See full document
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Senet Cnn Based Tomato Leaf Disease Detection
... V. CONCLUSION AND FUTURE WORK This paper focuses on to adapt a powerful and handy method that classifies the diseases of tomato leaf. SENet CNN technique is used for this motive. Attributes from the disease affected area ... See full document
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In-line recognition of agglomerated pharmaceutical pellets with density-based clustering and convolutional neural network
... a classification based not only on particle size but on a set of learned visual features that can better differentiate between primary particles (single or grouped) and real ... See full document
6
Brain Tumor Classification Using Convolutional Neural Networks
... Finally, the convolution neural network is used for automatic brain tumor classification. The brain image dataset is taken from image net. Image net is a one of the pre-trained model. If you want to ... See full document
5
The Unsupervised Gravitational Mass Weighted Probability PCA For Pixel-Wise And Sub-Pixel Wise Classification
... technique for hyperspectral data by using image fusion and recursive filtering method. The steps involved in this study are the following; initially, the hyperspectral images are divided into several subsets of ... See full document
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Implementation Of Data Augmentation In Convolutional Neural Network And Gradient Boosted Classifier For Vehicle Classification
... the convolutional neural net and the classifying principle of gradient boosted classifier, the paper assumes that the overfitting and the accuracy will be higher than the previous ...the ... See full document
5
A Novel Method for Remotely Sensed Hyperspectral Image Classification Based on Convolutional Neural Network
... HSI classification a challenging ...image classification may include determination of a suitable classification system, selection of training samples, image pre-processing, feature extraction, ... See full document
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Enhanced Self Organizing Map Neural Network for DNA Sequence Classification
... to sequence alignment [23-25], over time, GA and many variants of it have been applied to the sequence alignment ...for sequence alignment using evolutionary computation [26], which combined ant ... See full document
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Identification Of Weeds From Crops Using Convolutional Neural Network
... of network Architecture YannLeCun uses a new architecture which is good at object recognition in image dataset called the Convolutional Neural Network ...The convolutional technique is ... See full document
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