Recently, a variety of approaches have been enriching the field remote sensing (RS) image processing and analysis. Unfortunately, existing methods remain limited to rich spatiospectral content today's large data sets. It would seem intriguing resort deep learning (DL)-based at this stage with regard their ability offer accurate semantic interpretation data. However, specificity introduced by coexistence spectral spatial in RS sets widens scope challenges presented adapt DL these contexts....

This paper is concerned with the automatic detection of linear features in SAR satellite data, application to road network extraction. After a directional prefiltering step, morphological line detector presented. To improve performances, results obtained on multitemporal data are fused. Different fusion strategies involving different operators then Since extensions classical set union and intersection do not lead satisfactory (the corresponding either too indulgent or severe), first strategy...

In the hue saturation intensity (HSI) space, a difference taking into account relevance is defined. A gradient operator build up with this difference. Two color edge detectors are then proposed. These mix in different way H,S,I gradients. Experimental results presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

The physicochemical properties of a renewable diesel (RD) and several petroleum (PD)–dominant diesels were examined to assess the feasibility identifying quantifying presence RD biodiesel from PD their blends. Relative all PD-dominant diesels, exhibited lower density, higher flash point, reduced evaporation loss comparable viscosity water content. studied contained limited amount aromatics, with aliphatic hydrocarbons predominantly within C15 C18 range. Most individual detected in whereas...

This paper discusses the use of computer vision in interpretation human gestures. Hand gestures would be an intuitive and ideal way exchanging information with other people a virtual space, guiding some robots to perform certain tasks hostile environment, or interacting computers. can divided into two main categories: static dynamic In this paper, novel hand gesture recognition technique is proposed. It based on 2D skeleton representation hand. For each gesture, skeletons posture are...

In this paper we present a video summarization method based on the study of spatio-temporal activity within video. The visual is estimated by measuring number interest points, jointly obtained in spatial and temporal domains. proposed approach composed five steps. First, image features are collected using Hessian matrix. Then, these processed to retrieve candidate segments for summary (denoted clips). Further on, two specific steps designed first detect redundant clips, second eliminate...

With the implementation of stringent environmental regulations, high sulfur fuel oils (HSFO) are shifted to very low (VLSFOs) and ultralow (ULSFOs). The current understanding these fuels is far from sufficient. chemical fingerprints significantly altered by desulfurization processes, sulfur-containing compounds present in or extremely concentrations. These changes pose challenges for petroleum analysis. ULSFOs studied were limited distillates. Like conventional oils, diverse. do not just...

A novel method for color image enhancement is proposed as an extension of the scalar-diffusion–shock-filter coupling model, where noisy and blurred images are denoised sharpened. The model based on using single vectors gradient magnitude second derivatives a manner to relate different components image. This can be viewed generalization Bettahar–Stambouli filter multivalued images. algorithm more efficient than mentioned some previous works at denoising deblurring without creating false colors.

The Cherenkov Telescope Array is the future of ground-based gamma-ray astronomy. Its first prototype telescope built on-site, Large Size 1, currently under commissioning and taking its scientific data. In this paper, we present for time development a full-event reconstruction based on deep convolutional neural networks application to real We show that it outperforms standard analysis, both simulated data, thus validating approach CTA data analysis. This work also illustrates difficulty...

In the computer vision field, semantic segmentation represents a very interesting task.Convolutional Neural Network methods have shown their great performances in comparison with other methods.In this paper, we propose multiscale fully convolutional DenseNet approach for segmentation.Our is based on successful method.It reinforced by integrating kernel prediction after last dense block which performs model averaging over different spatial scales and provides more flexibility of our network...

In this paper an improved cut detection algorithm, adapted to the segmentation of animation movies, is proposed. As color a major feature movies (each movie has its own particular distribution) proposed algorithm applies second order derivatives on Euclidean distances between histograms frames quadrants in improve detection. For frame classification, automatic threshold estimation Also, reduce false detections, we propose detect effect specific named "short change" (i.e. thunders,...

With the rapid development of Remote Sensing acquisition techniques, there is a need to scale and improve processing tools cope with observed increase both data volume richness. Among popular techniques in remote sensing, Deep Learning gains increasing interest but depends on quality training data. Therefore, this paper presents recent approaches for fine or coarse land cover semantic segmentation estimation. Various 2D architectures are tested new 3D model introduced order jointly process...

The present paper introduces convolution and pooling operators for indexed images. These can be used on images that do not provide Cartesian grids of pixels, as long a list neighbor’s indices provided each pixel. They are foreseen being useful convolutional neural networks (CNN) applied to special sensors, especially in science, without requiring image pre-processing. work explains the method its implementation Pytorch framework shows an application kernels classification task with hexagonal...

This paper investigates how the detection of diverse high-level semantic concepts (objects, actions, scene types, persons etc.) in videos can be improved by applying a model human retina. A large part current approaches for Content-Based Image/Video Retrieval (CBIR/CBVR) relies on Bag-of-Words (BoW) model, which has shown to perform well especially object recognition static images. Nevertheless, state-of-the-art framework shows its limits when applied because added temporal information. In...