[PDF] Top 20 Research on road extraction of remote sensing image based on convolutional neural network
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Research on road extraction of remote sensing image based on convolutional neural network
... information. Road information extraction plays an important role in traffic management, urban planning, automatic vehicle navigation, and emergency ...of remote sensing technology, the quality ... See full document
11
LAYOUT AN INEXPENSIVE ELLIPTICAL POLARIZED PRODUCTIVE INTEGRATED TRANSCEIVER
... satellite image of high resolution can help in road navigation, update geographic information systems, emergency rescue system that requires instantaneous ...a road from its ...more research ... See full document
11
Image Description using Deep Neural Networks
... Recent research [9, 13-15] has demonstrated state-of-the-art image captioning results using deep learning ...the network. Convolutional Neural Networks (CNNs) are deployed for visual ... See full document
97
Multiple Object Extraction of Remote Sensing Images Based on Convolutional Neural Networks and Support Vector Machines
... Multiple Object Extraction of Remote Sensing Images Based on Convolutional Neural Networks and Support Vector Machines Tao-xing FENG, Wei-yu WANG, Xiao-meng QIAN, Zhan-hong ZHANG, Hui LI[r] ... See full document
11
A Model of Extracting Building from High Resolution Remote Sensing Image Based on Bayesian Convolutional Neural Networks
... The experiment site are selected in Zhangqiu city of Shandong Province Mingshui town, there is a certain interval between different residents. The buildings in the residential area are mostly flat or two storeys ... See full document
12
Image Segmentation Using Convolutional Neural Network
... the image is done automatically by the ...in remote sensing images taken by ...spectral remote sensing data, kernels are designed according to ...case based reasoning and CNN ... See full document
9
Automatic diagnosis of imbalanced ophthalmic images using a cost-sensitive deep convolutional neural network
... feature extraction methods [27, 29] (LBP, WT, SIFT, and COTE), two excellent classifiers [support vector machine (SVM) and random forest (RF)] and three data-level methods [18, 19, 22] [the synthetic minority ... See full document
20
Cloud Detection via Convolutional Neural Network in Visible Light Remote Sensing Images
... In this paper, we propose a method based on convolutional neural network for cloud detection in visible light remote sensing images. Our method can automatically extract the ... See full document
6
Enhancement of the Satellite Images using ACO and DNN Approach
... Abstract: Image classification is a vital technique used to remote-sensing for the pattern identification and design analysis of the satellite information in the form of ...etc. Image ... See full document
9
A Road Extraction Method Based on Region Growing and Mathematical Morphology from Remote Sensing Images
... population, road traffic problems such as traffic jam and traffic accident have become the bottleneck which re- stricts economic ...extract road information to com- pute the degree of road damage for ... See full document
7
Aircraft detection in remote sensing images based on saliency and convolution neural network
... The second category is the template matching method for aircraft detection. Considering that the size and shape of the aircraft is similar between the same types of aircraft, researcher design the various shape templates ... See full document
16
Remote sensing scene classification based on rotation-invariant feature learning and joint decision making
... images, remote sensing scene classification has always been a hot research topic in its related ...of remote sensing datasets including the small scale of scene classes, the lack of ... See full document
11
A Novel Registration Method for High Resolution Remote Sensing Images Based on JSEG and NMI
... resolution remote sensing image registration, difficulties and limitations are common in selection of directional sub-bands and distribution optimization of control point pairs ...method based ... See full document
18
Identification Of Weeds From Crops Using Convolutional Neural Network
... input image which helps to optimize the number of hyper parameters in the architecture and supports in improving the computation efficiency of the ...varieties based on its commonality and it also able to ... See full document
6
A Content-Based Remote Sensing Image Change Information Retrieval Model
... Server Image Extension, which accesses the USGS and NASA created 34,000 scenes of Global Land Survey (GLS) Landsat imagery, comprising of worldwide imagery from the 1970s, 1990s, 2000 and ...the remote ... See full document
17
A Radon-based Convolutional Neural Network for Medical Image Retrieval
... Step 4: image retrieval is the main aim of this step. Suppose a test query is selected. This query goes through the proposed chain of processing. Figure 6 depicts, 90 equidistant Radon projections of the computed ... See full document
6
Histopathological Biopsy Image Classification Based On Convolutional Neural Network
... In the reference by O. Sertel et al. [4], the procedure proposed has assembled the image into an occasional or excessive grade on the premise of the degree of cytological segments present in it. For division ... See full document
6
In-line recognition of agglomerated pharmaceutical pellets with density-based clustering and convolutional neural network
... determined based on the weight of dry materials entering the coat- ing process (the mass of the particles and the dry coating dispersion mass) and on the weight of dry materials exit- ing the coating process (the ... See full document
6
Unmanned Aerial Vehicle Remote Sensing Monitoring And Image Acquisition System
... Panoramic image seamless real-time splicing technology in this system is specific to multi lens seamless real-time splicing ...the image feature points is the first step to achieve multi lens seamless real- ... See full document
5
Convolutional neural network-based automatic image recognition for agricultural machinery
... on image transformation using the image’s invariant moment, ...accelerate network convergence performance, and improve network calculation ... See full document
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