[PDF] Top 20 Light field Image Super resolution Using Convolutional Neural Network
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Light field Image Super resolution Using Convolutional Neural Network
... a light field super-resolution method based on ...for light field ...the light field image, next step we will discuss how to improve the angular ...to ... See full document
5
A Novel Approach Using Convolutional Neural Network to Reconstruct Image resolution
... Extensively, image super-resolution (SR) poses a challenge across all fields of interest as its problem is considered inherent in its acquisition due to several ...Randomized Convolutional ... See full document
13
Classification of Crease Features from Interdigital and Hypothenar Regions of Palmprint Image for Race Identification using Convolutional Neural Network
... low-resolution image and therefore it has attracted attention from researchers in biometric recognition ...the field of biometric ...analyzed using multiple sets of test data ... See full document
7
Image Reconstruction Using Super Resolution and Back-propagation Neural Networks
... single image super resolution (SR) is ...low resolution (LR) images and desired high resolution (HR) image as multi-scale markov random field ...artificial neural ... See full document
7
Super Sparse Convolutional Neural Networks
... novel super sparse convolutional (SSC) kernel, and its corresponding network is called ...point-wise” convolutional operations without any spa- tial kernels ...low resolution ImageNet ... See full document
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Object Detection using Convolutional Neural Network in the Application of Supplementary Nutrition Value of Fruits
... algorithm using multiple structures identical intensity, color, alignment and edge of the fruit ...the image FFB, the expansion of out-of-doors image inspection of oil palm fruit fresh bunches (FFB) ... See full document
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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 ...the field of agriculture, so that they can spray it ... See full document
6
Single Image Super-Resolution
... an image. Kernels in convolutional network represent a fea- ture extracting method, which constrains a set of ...a convolutional layer is called the depth of this ...in neural ... See full document
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Research on road extraction of remote sensing image based on convolutional neural network
... road network information plays a very important role in traffic management, urban plan- ning, automatic vehicle navigation, and emergency man- agement ...[3]. Using the computer to extract road information ... See full document
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Super Resolution Land Cover Pattern Prediction Using a Hopfield Neural Network
... of field boundaries with subpixel ...spatial resolution of satellite sensor ...spatial resolution and the models used still have problems resolving image pixels containing more than two ... See full document
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Super Resolution Imaging of Mammograms Based on the Super Resolution Convolutional Neural Network
... a super-resolution scheme based on the su- per-resolution convolutional neural network (SRCNN) for enhancing image resolution in digital ...the ... See full document
16
Deep-learning-based motion-correction algorithm in optical resolution photoacoustic microscopy
... by using a backpropagation algorithm to indicate how a net should change its internal parameters, which are used to compute the representation in each layer from that in the previous ...A convolutional ... See full document
6
Deep Convolution Neural Networks for Automatic Eyeglasses Removal
... the Super Resolution Convolutional Neural Network (SRCNN) proposed by Dong [6] shows the great potential of an end-to-end DCN in image super- ...the network ... See full document
8
Automatic Plastic Waste Segregation And Sorting Using Deep Learning Model
... an image classification on it, the development of a CNN based object detector became ...based image classifiers were computationally very expensive compared traditional techniques like HAAR ...for ... See full document
5
Search | Preprints
... Precipitation Estimation Using Convolutional Neural Network. Water Resources Research[r] ... See full document
37
Image Enhancement Using Wavelet Decomposition, Super Resolution Algorithm & LUM Filters
... In image resolution enhancement smoothing caused by using interpolation, the main loss is on its high frequency components ...the super resolved image, preserving the edges is ...the ... See full document
5
Comparative Evaluation of Deep Architectures for Face Recognition in Unconstrained Environment (FRUE)
... face image database containing around 494,414 images of 10,575 unique identities, which is made publicaly available, and training CNN for the collected ...10 convolutional layer, 5 pooling layer and 3 fully ... See full document
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LAYOUT AN INEXPENSIVE ELLIPTICAL POLARIZED PRODUCTIVE INTEGRATED TRANSCEIVER
... one field where machine learning has been extensively used with commendable success ...Artificial Neural Networks as a prospective solution for approaching the road extraction ... See full document
11
Super-Resolution of an Image using Examplar Technique
... in image processing applications as a result of the large quantity of low resolution video and image ...material. Super resolution image reconstruction may be a promising ... See full document
8
Image Super Resolution Using Wavelet Analysis
... lower resolution are generated by low-pass filtering process of the higher resolution ...low resolution component of the input original ...sub-band image, having information which is less in ... See full document
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