Search results for "Convolution"
showing 10 items of 334 documents
Deep Learning for Resource-Limited Devices
2020
In recent years, deep neural networks have revolutionized the development of intelligent systems and applications in many areas. Despite their numerous advantages and potentials, these intelligent models still suffer from several issues. Among them, the fact that they became very complex with millions of parameters. That is, requiring more resources and time, and being unsuitable for small restricted devices. To contribute in this direction, this paper presents (1) some state-of-the-art lightweight architectures that were specifically designed for small-sized devices, and (2) some recent solutions that have been proposed to optimize/compress classical deep neural networks to allow their dep…
Full Reference Mesh Visual Quality Assessment Using Pre-Trained Deep Network and Quality Indices
2019
In this paper, we propose an objective quality metric to evaluate the perceived visual quality of 3D meshes. Our method relies on pre-trained convolutional neural network i.e VGG to extract features from the distorted mesh and its reference. Quality indices from well-known mesh visual quality metrics are concatenated with the extracted features resulting a global feature vector. this latter is used to learn the support vector regression (SVR) to predict the final quality score. Experimental results from two subjective databases (LIRIS masking database and LIRIS/EPFL general-purpose database) and comparisons with seven objective metrics cited in the state-of-the-art demonstrate the effective…
Extended Depth-of-Field 3-D Display and Visualization by Combination of Amplitude-Modulated Microlenses and Deconvolution Tools
2005
One of the main challenges in 3-D display and visualization is to overcome its limited depth of field. Such limitation is due to the fast deterioration of lateral resolution for out-of-focus object positions. Here we propose a new method to significantly extend the depth of field. The method is based on the combined benefits of a proper amplitude modulation of the microlenses, and the application of deconvolution tools. Numerical tests are presented to verify the theoretical analysis.
Automatic Detection of Infantile Hemangioma using Convolutional Neural Network Approach
2020
Infantile hemangioma is the most common tumor of childhood. This study proposes an automatic detection as a preliminary step for a further accurate monitoring tool to evaluate the clinical status of hemangioma. For the detection of hemangioma pixels, a convolutional neural network (CNN) was trained on patches of two classes (hemangioma and nonhemangioma) from the train dataset, and then it was used to classify all the pixels of the region of interest from the test dataset. In order to evaluate the results of segmentation obtained with CNN, the region of interest of the test dataset was also segmented using two classical methods of segmentation: fuzzy c-means clustering (FCM) and segmentatio…
A Sentiment Enhanced Deep Collaborative Filtering Recommender System
2021
Recommender systems use advanced analytic and learning techniques to select relevant information from massive data and inform users’ smart decision-making on their daily needs. Numerous works exploiting user’s sentiments on products to enhance recommendations have been introduced. However, there has been relatively less work exploring higher-order user-item features interactions for sentiment enhanced recommender system. In this paper, a novel Sentiment Enhanced Deep Collaborative Filtering Recommender System (SE-DCF) is developed. The architecture is based on a Neural Attention network component aggregated with the output predictions of a Convolution Neural Network (CNN) recommender. Speci…
Reduced Reference Mesh Visual Quality Assessment Based on Convolutional Neural Network
2018
3D meshes are usually affected by various visual distortions during their transmission and geometric processing. In this paper we propose a reduced reference method for mesh visual quality assessment. The method compares features extracted from the distorted mesh and the original one using a convolutional neural network in order to estimate the visual quality score. The perceptual distance between two meshes is computed as the Kullback-Leibler divergence between the two sets of feature vectors. Experimental results from two subjective databases (LIRIS masking database and LIRIS/EPFL general purpose database) and comparisons with seven objective metrics cited in the state-of-the-art demonstr…
Deep learning model deploying on embedded skin cancer diagnostic device
2020
The number of research papers, where neural networks are applied in medical image analysis is growing. There is a proof that Convolutional Neural Networks (CNN) are able to differentiate skin cancer from nevi with greater accuracy than experienced specialists on average (sensitivity 82% and 73% accordingly).1 Team's latest research2 allows achieving even greater accuracy, by using specific narrow-band illumination. Nevertheless, the overall probability of early skin cancer detection depends on the availability of diagnostic tools. If screening tools will be available to a high number of general practices, the chance of disease detection will increase. The previous research3 shows that scala…
Crystallization kinetics in relation to polymer processing
1993
Phase distribution of quenched samples has been determined by a deconvolution procedure of WAXS spectra in a wide range of cooling rates. The informations collected together with isothermal and DSC results provide a very wide set of data on the crystallization kinetics of polymers relevant which covers conditions encountered in most polymer processing operations. They have been compared with predictions of a non-isothermal crystallization model assuming two independent and parallel crystallization processes competing during solidification.
Structure of bottle-brush polymers in solution: A Monte Carlo test of models for the scattering function
2008
Extensive Monte Carlo results are presented for a lattice model of a bottle-brush polymer under good solvent or Theta solvent conditions. Varying the side chain length, backbone length, and the grafting density for a rigid straight backbone, both radial density profiles of monomers and side chain ends are obtained, as well as structure factors describing the scattering from a single side chain and from the total bottle-brush polymer. To describe the structure in the interior of a very long bottle-brush, a periodic boundary condition in the direction along the backbone is used, and to describe effects due to the finiteness of the backbone length, a second set of simulations with free ends of…