Search results for "Image"
showing 10 items of 6818 documents
Learning Flow-Based Feature Warping for Face Frontalization with Illumination Inconsistent Supervision
2020
Despite recent advances in deep learning-based face frontalization methods, photo-realistic and illumination preserving frontal face synthesis is still challenging due to large pose and illumination discrepancy during training. We propose a novel Flow-based Feature Warping Model (FFWM) which can learn to synthesize photo-realistic and illumination preserving frontal images with illumination inconsistent supervision. Specifically, an Illumination Preserving Module (IPM) is proposed to learn illumination preserving image synthesis from illumination inconsistent image pairs. IPM includes two pathways which collaborate to ensure the synthesized frontal images are illumination preserving and wit…
Multiscale Attention-Based Prototypical Network For Few-Shot Semantic Segmentation
2021
International audience; Deep learning-based image understanding techniques require a large number of labeled images for training. Few-shot semantic segmentation, on the contrary, aims at generalizing the segmentation ability of the model to new categories given only a few labeled samples. To tackle this problem, we propose a novel prototypical network (MAPnet) with multiscale feature attention. To fully exploit the representative features of target classes, we firstly extract rich contextual information of labeled support images via a multiscale feature enhancement module. The learned prototypes from support features provide further semantic guidance on the query image. Then we adaptively i…
Proposition of Convolutional Neural Network Based System for Skin Cancer Detection
2019
Skin cancer automated diagnosis tools play a vital role in timely screening, helping dermatologists focus on melanoma cases. Best arts on automated melanoma screening use deep learning-based approaches, especially deep convolutional neural networks (CNN) to improve performances. Because of the large number of parameters that could be involved during training in CNN many training samples are needed to avoid overfitting problem. Gabor filtering can efficiently extract spatial information including edges and textures, which may reduce the features extraction burden to CNN. In this paper, we proposed a Gabor Convolutional Network (GCN) model to improve the performance of automated diagnosis of …
Combination Of Handcrafted And Deep Learning-Based Features For 3d Mesh Quality Assessment
2020
We propose in this paper a novel objective method to evaluate the perceived visual quality of 3D meshes. The proposed method in no-reference, it relies only on the distorted mesh for the quality estimation. It is based on a pre-trained convolutional neural network (i.e VGG to extract features from the distorted mesh) and handcrafted features extracted directly from the 3D mesh (i.e curvature and dihedral angle). A General Regression Neural Network (GRNN) is used to learn the statistical parameters of the feature vectors and estimate the quality score. Experimental results from for subjective databases (LIRIS masking, LIRIS/EPFL generalpurpose, UWB compression and LEETA simplification) and c…
No-reference mesh visual quality assessment via ensemble of convolutional neural networks and compact multi-linear pooling
2020
Abstract Blind or No reference quality evaluation is a challenging issue since it is done without access to the original content. In this work, we propose a method based on deep learning for the mesh visual quality assessment without reference. For a given 3D model, we first compute its mesh saliency. Then, we extract views from the 3D mesh and the corresponding mesh saliency. After that, the views are split into small patches that are filtered using a saliency threshold. Only the salient patches are selected and used as input data. After that, three pre-trained deep convolutional neural networks are employed for feature learning: VGG, AlexNet, and ResNet. Each network is fine-tuned and pro…
Design Space Exploration for a Custom VLIW Architecture: Direct Photo Printer Hardware Setting Using VEX Compiler
2008
Increasingly more computing power is demanded for contemporary applications such as multimedia, 3D visualization, and telecommunication. This paper presents a design space exploration (DSE) experience for an embedded VLIW processor that allows finding out the best architecture for given application. The proposed method has been implemented and tested using an image processing chain for direct photo printer. Our results show a considerable improvement in hardware cost and performance. After the best architecture is identified, we applied a technique to optimize the code in VEX system that uses ?inlining? function in order to reduce execution time.
Design and development of a fNIRS system prototype based on SiPM detectors
2014
Functional Near Infrared Spectroscopy (fNIRS) uses near infrared sources and detectors to measure changes in absorption due to neurovascular dynamics in response to brain activation. The use of Silicon Photomultipliers (SiPMs) in a fNIRS system has been estimated potentially able to increase the spatial resolution. Dedicated SiPM sensors have been designed and fabricated by using an optimized process. Electrical and optical characterizations are presented. The design and implementation of a portable fNIRS embedded system, hosting up to 64 IR-LED sources and 128 SiPM sensors, has been carried out. The system has been based on a scalable architecture whose elementary leaf is a flexible board …
Affine Illumination Compensation on Hyperspectral/Multiangular Remote Sensing Images
2011
The huge amount of information some of the new optical satellites developed nowadays will create demands to quickly and reliably compensate for changes in the atmospheric transmittance and varying solar illumination conditions. In this paper three different forms of affine transformation models (general, particular and diagonal) are considered as candidates for rapid compensation of illumination variations. They are tested on a group of three pairs of CHRISPROBA radiance images obtained in a test field in Barrax (Spain), and where there is a difference in the atmospheric as well as in the geometrical acquisition conditions. Results indicate that the proposed methodology is satisfactory for …
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…
A real-time auto calibration technique for stereo camera
2020
Calibration of the internal and external parameters of a stereo vision camera is a well-known research problem in the computer vision. Usually, to get accurate 3D results the camera should be manua...