[PDF] Top 20 Aircraft detection in remote sensing images based on saliency and convolution neural network
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Aircraft detection in remote sensing images based on saliency and convolution neural network
... Object detection automatic in remote sensing images has always been a hot ...deep convolution network based on region proposal for detection, there are many ... See full document
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Aircraft Detection in Remote Sensing Images via CNN Multi scale Feature Representation
... our aircraft detection method is illustrated in Figure ...large-size images into patches using two different scales sliding ...SSD network takes all the training image patches as input for ... See full document
12
Unsupervised Change Detection in Remote Sensing Images Using Pulse Coupled Neural Network
... change detection in multitemporal satellite images of same scene using Pulse coupled neural ...artificial neural network which is developed in 1990 and based on visual cortex of ... See full document
7
Research on road extraction of remote sensing image based on convolutional neural network
... of remote sensing technology, the quality of high-resolution satellite images is improved and more easily obtained, which makes it possible to use remote sensing images to locate ... See full document
11
Contribution of Artificial Neural Networks to the Identification and Detection of Targets Concerning Mobility on Remote Sensing Images
... Topographic maps are still widely used in military field principally for preparing forces movement on unknown territory. Indeed, the movement of ground vehicles, especially in wartime, is generally based on ... See full document
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Satellite Remote Sensing Image Based Aircraft Recognition Using Transform Features and Detection Using Fuzzy Clustering K Pavan Kumar & D Rajesh Setty
... neurons. Neural networks, with their extraordinary capacity to derive that means from complex or obscure records, may be used to extract patterns and locate trends which are too complicated to be noticed through ... See full document
7
Evaluation of Adaptive Boosting and Neural Network in Earthquake Damage Levels Detection
... using remote sensing ...using remote sensing data can be divided into three ...event images to determine the extent of earthquake ...uses images that are taken after earthquake ... See full document
7
Research on Rotor Winding Detection Based on Texture Information and Convolution Neural Network
... quality based on machine vision; ...Convolutional neural network as a trainable feature extractor and random forest as a pattern recognizer to implement a hybrid method based on deep ... See full document
5
Cloud Detection via Convolutional Neural Network in Visible Light Remote Sensing Images
... For our method, we obtain much higher accuracy than the methods which only use gray features and manually extracted GLCM features by comparing CNN and SVM(threshold + mean gray value + GLCM). This indicates that our ... See full document
6
CONVOLUTION NEURAL NETWORK (CNN) BASED OBJECT DETECTION IN OCEANOGRAPHIC IMAGERY
... satellite images. The remote senogrpahy techniques are always efficient in making the detection of such objects quite ...texture based technique has been proposed along with the neural ... See full document
5
Crop Detection and Classification using Remote Sensing Images
... of remote sensing ...RS images are utmost beneficial for agricultural ...crop detection and classification utilizing RS ...crop detection and classification techniques like, review on ... See full document
9
Aircraft Identification in High Resolution Remote Sensing Images using Shape Analysis
... Automatic aircraft recognition in a complex environment has long been an interesting and challenging ...Conventional aircraft recognition methods always extract the overall shape features of aircraft ... See full document
7
Research on an Edge Detection Algorithm of Remote Sensing Image Based on Wavelet Enhancement and Morphology
... morphology is presented. And some experiments were taken to validate it. The experimental results show that our method can achieve the better edge detection result and has a good anti-noise property. It is more ... See full document
6
Detection of Saliency for Binocular Images
... Many saliency detection models of stereoscopic display require multi resolution representation of map data in new models for salient region extraction that is not possible in spectral ...enhanced ... See full document
9
An Novel Framework For Content Based Image Retrieval With Quality Assessment System using Optimal Deep Convolution Neural Network
... Content based image retrieval (CBIR) models become popular for retrieving images connected to the query image (QI) from massive ...extraction based CBIR ...the images with maximum resemblance ... See full document
11
1. Efficient face recognition using convolutional neural networks
... Artificial Neural Networks (ANNs)[22,23,24] are processing devices that are modeled after the neural structure of the mammalian cerebral cortex on smaller ...scales. Neural networks are typically ... See full document
7
Graph convolutional networks: a comprehensive review
... as images and text data, and (2) for graph-structured data, the underlying connectivity patterns are often complex and ...graph neural networks) have recently emerged in machine learning and other related ... See full document
23
Wideband spectrum sensing using adaptive neuro fuzzy inference system in cognitive radio networks
... energy detection, spectrum sensing based on HSMM and fuzzy neural network based spectrum sensing are plotted versus the false-alarm probability for a detection ... See full document
6
Design and Implementation of Intelligent Recommendation System for Farmers using CNN and RNN
... classification based on image segmentation in precision agriculture using hyperspectral ...images. Images were acquired using the CASI sensor and statistical comparison is used to determine the mean ... See full document
5
Change Detection in Remote Sensing Images Using Elitist Genetic Algorithm
... change detection methods have been demonstrated to be effective in constrained processing environments with predictable ...Proper detection of changes in these images is very important for separating ... See full document
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