[PDF] Top 20 Exploring Transfer Learning via Convolutional Neural Networks for Image Classification and Super-Resolution
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Exploring Transfer Learning via Convolutional Neural Networks for Image Classification and Super-Resolution
... Herk ¨ommlicherweise verwenden Verfahren des maschinellen Lernens den gleichen Merk- malsraum und die gleiche Verteilung zum Trainieren und Testen der abgewendeten Meth- oden. Mehrere Probleme k ¨onnen bei diesem Ansatz ... See full document
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Lesion Classification in Mammograms Using Convolutional Neural Networks and Transfer Learning
... benign and 310 malign mass lesions) from 344 ...MLO and CC views with image size of 720×1168 (width×height) pixels and a bit depth of 8 bits per pixel in TIFF format; included are also ... See full document
9
Convolutional neural networks for transient candidate vetting in large-scale surveys
... variable and transient astronomical ...machine learning algorithms to classify the detected objects and to filter out the most interesting ...high-precision classification systems essential to ... See full document
15
3D face recognition with descriptor images and shallow convolutional neural networks
... accurately and quickly identify a ...high resolution 2D face images captured by low cost cam- eras, in a secret way, at a distance and without cooperation from the people being ...illumination ... See full document
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Retinal image quality assessment using deep convolutional neural networks
... Deep Learning is a subset of a more general field of artificial intelligence called machine learning, which is predicated on this idea of learning from ...Deep Learning, instead of teaching a ... See full document
182
Ant genera identification using an ensemble of convolutional neural networks
... taxa and an insufficient number of taxonomists to identify a great deal of col- lected ...Machine learning tools, particularly convolutional neural networks (CNNs), are then welcome to ... See full document
14
Comparative Study of First Order Optimizers for Image Classification Using Convolutional Neural Networks on Histopathology Images
... cancerous and non-cancerous images, and is capable of recognizing the relevant image without being explicitly programmed to do so, and using a performance measure like the AUC of the ROC ... See full document
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SINGLE-IMAGE SUPER RESOLUTION FOR MULTISPECTRAL REMOTE SENSING DATA USING CONVOLUTIONAL NEURAL NETWORKS
... (2014) and our own experiments in Section ...end learning, the parameters in turn only depend on the provided training ...single-image super resolution for multispectral remote sensing ... See full document
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Deep learning for single image super-resolution using residual image learning and multiple degradations
... deep convolutional neural networks (CNNs) and Generative Adversarial Networks (GANs) applied in single image super-resolution (SISR) ...lower resolution (LR) ... See full document
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Transfer learning with convolutional neural networks for diabetic retinopathy image classification
... availability and its size, followed by the Messidor ...], and Lam et al. [ 62 ] considered a binary classification task due to the lack of a sufficient number of images for some of the ...in ... See full document
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Lesion classification in mammograms using convolutional neural networks and transfer learning
... model and no normalisation, surpassing the result of ...images and an SVM instead of a softmax layer (since they considered that the former had better performance as classi fier than the ...normalised ... See full document
8
Rotated Filters and Learning Strategies in Convolutional Neural Networks for Mammographic Lesions Detection
... CC and MLO ...train and can overfit more easily if the amount of data is not ...mammogram and two binary images with lesion segmentation per view, and integrated the information at a later ... See full document
105
A novel architecture to classify histopathology images using convolutional neural networks
... architecture and the architecture proposed by Bayramoglu et ...layer and the second before the fully connected ...RMSprop and Adam ...layer and the dropout layer in the middle of the ... See full document
17
A PROTOTYPE FOR CLASSIFICATION OF CLASSICAL MUSIC USING NEURAL NETWORKS
... Our first goal was to discriminate between three genres of instrumental music: music for flute, piano and violin. The 6s’ segments extracted were chosen so as to include soles from each instrument by single or ... See full document
6
Estimating image aesthetic value using a content-based convolutional neural network architecture
... broadness and complexity of the criteria used by each one to define what is ...[17] and websites like ...datasets and websites gather information, like the number of likes received by an image ... See full document
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Image Classification and Optimized Image Reproduction
... areas, and low-key images in the dark areas of the tone scale is quite ...actual image processing. An analysis of the pixel numbers in an image in the L*-scale generates suggested borders which can ... See full document
5
Improving Convolutional Neural Network Design via Variable Neighborhood Search
... The comparison between the studied approaches indicates that S1 shows the best compromise between loss and accuracy improvement as function of the number of training epochs. For this model, shown in Eq. 7, a ... See full document
9
Crackle and wheeze detection in lung sound signals using convolutional neural networks
... It is worthy to note that although the MFCC method is one of the standards in the state of the art in signal processing, it didn’t generalize as well as was expected. The MFCC method utilizes the discrete cosine ... See full document
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Segmentation and classification of leukocytes using neural networks: a generalization direction
... supervised neural net extracting the general fea- tures that are necessary to have success in the segmentation of images that are not in the training ...images and when the segmentation method is not ... See full document
25
Convolutional and recurrent neural networks in time-series applied to injection molding processes
... C and the operation temperature of the injection molding machine inside the chamber is around 60 ◦ C, so it is not possible to position this camera inside the chamber for a permanent solution in an industrial ... See full document
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