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[PDF] Top 20 Exploring Deep Neural Network Models for Classification of High-resolution Panoramas

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Exploring Deep Neural Network Models for Classification of High-resolution Panoramas

Exploring Deep Neural Network Models for Classification of High-resolution Panoramas

... plant classification system which can show acceptable Precision and Recall for unseen test ...plants classification approaches using Precision Vs Recall ...a classification method which keeps false ... See full document

82

Adaptation and contextualization of deep neural network models

Adaptation and contextualization of deep neural network models

... of Deep Neural Networks (DNNs) to provide very high accuracy in classification and recognition problems makes them the major tool for developments in such ...efficient classification of ... See full document

8

Intrusion detection and classification with autoencoded deep neural network

Intrusion detection and classification with autoencoded deep neural network

... on exploring low latency models while maintain- ing high accuracy by proposing a hybrid deep neural network that includes an unsupervised pre-training using autoencoders to make ... See full document

16

Intrusion Detection and Classification with Autoencoded Deep Neural Network

Intrusion Detection and Classification with Autoencoded Deep Neural Network

... on exploring low latency models while maintain- ing high accuracy by proposing a hybrid deep neural network that includes an unsupervised pre-training using autoencoders to make ... See full document

16

Cough event classification by pretrained deep neural network

Cough event classification by pretrained deep neural network

... probability neural net- work, principle component analysis was employed to reduce the feature ...filler models ” ...the high energy audio parts, the whole algorithm achieved an average 85% ... See full document

10

High resolution paleovalley classification from airborne electromagnetic imaging and deep neural network  training using digital elevation model data

High resolution paleovalley classification from airborne electromagnetic imaging and deep neural network training using digital elevation model data

... Artificial neural networks (ANNs), which can express the complex and nonlinear relationship between input and out- puts, were previously applied for the inversion of EC values from original AEM data (Ahl, 2003) ... See full document

20

Glioblastoma Multiforme Classification On High Resolution Histology Image Using Deep Spatial Fusion Network

Glioblastoma Multiforme Classification On High Resolution Histology Image Using Deep Spatial Fusion Network

... the deep network using shortcut connections and by residual ...to high level are combined to make final predictions, where as discriminative features are distributed in the image from cellular to ... See full document

13

Multi-Column Deep Neural Network for Traffic Sign Classification

Multi-Column Deep Neural Network for Traffic Sign Classification

... Keywords: deep neural networks, image classification, traffic signs, image preprocessing ...the high in-class variability of many object types. Deep hierarchical neural ... See full document

15

Big Data Classification Based On Forest Deep Neural Network

Big Data Classification Based On Forest Deep Neural Network

... to high parallelism and cost few I/O. The ELM sub models were trained parallel with the distributed data blocks on the cluster and integrated as a complete single hidden layer feed forward neural ... See full document

5

Building Extraction from Very High Resolution Aerial Imagery Using Joint Attention Deep Neural Network

Building Extraction from Very High Resolution Aerial Imagery Using Joint Attention Deep Neural Network

... the network. Therefore, the difference between deep layer and shallow layer in the use of context information leads to the variation of classification ...corresponding deep layers in the skip ... See full document

21

Deep Learning Approach Model for Vehicle Classification using Artificial Neural Network 

Deep Learning Approach Model for Vehicle Classification using Artificial Neural Network 

... detection, classification and time based analytical ...and classification are the models utilized primarily for the vehicular traffic surveillance, data collection and relevant ...and ... See full document

7

Deep convolutional neural network based medical image classification for disease diagnosis

Deep convolutional neural network based medical image classification for disease diagnosis

... simple network usually cannot learn enough from the data, and therefore cannot get high ...complex network is hard to train and tends to overfit ...a network model with proper size and other ... See full document

18

Deep neural network models for image classification and regression

Deep neural network models for image classification and regression

... 88 In Chapter 4, we describe the developed methods for chemometric data analysis based on CNN. In particular, we modify the standard CNN architecture to adapt it to 1D input data. The proposed 1D-CNN architecture is thus ... See full document

98

Deep Neural Network Language Models

Deep Neural Network Language Models

... with deep neural networks. We followed the feed-forward neural network architecture and made the network deeper with the addition of several lay- ers of ...with deep networks ... See full document

9

Watermarking Federated Deep Neural Network Models

Watermarking Federated Deep Neural Network Models

... Adversarial examples as watermark Adversarial examples can also be used as watermarks. For example, authors in [43] propose a zero-bit watermarking algorithm to embed zero-bit watermarks into remote models. This ... See full document

69

Application of Deep Neural Network for Diabetes Classification and Prediction

Application of Deep Neural Network for Diabetes Classification and Prediction

... EXPLANATION Deep learning comes under the category of machine learning ...In deep neural networks feature extraction and classification are not explicitly ...Recurrent neural ... See full document

7

Deep Markov Neural Network for Sequential Data Classification

Deep Markov Neural Network for Sequential Data Classification

... a Deep Markov Neu- ral Network (DMNN) for incorporating sequential data and arbitrary features into language model- ...current neural networks, such as the vanishing gra- dient ... See full document

6

Hybrid Approach for Imbalanced Classification with Deep Neural Network

Hybrid Approach for Imbalanced Classification with Deep Neural Network

... Figure 3: SMOTE synthetic sample for class 5 With the generated synthetic samples as additional training data, we train it using our neural network. In the input layer, we expect each sample to be a ... See full document

7

Review of deep convolution neural network in image classification

Review of deep convolution neural network in image classification

... with deep learning and intensive learning is still in its infancy, but some research in this area has achieved good performance in multi- object recognition tasks and video game ...the neural network ... See full document

6

Relation Classification via Convolutional Deep Neural Network

Relation Classification via Convolutional Deep Neural Network

... vector models are severely limited because they do not capture long distance features and semantic com- positionality, the important quality of natural language that allows humans to understand the meanings of a ... See full document

10

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