Hybrid image representation methods for automatic image annotation: a survey

In most automatic image annotation systems, images are represented with low level features using either global methods or local methods. In global methods, the entire image is used as a unit. Local methods divide images into blocks where fixed-size sub-image blocks are adopted as sub-units; or into regions by using segmented regions as sub-units in images. In contrast to typical automatic image annotation methods that use either global or local features exclusively, several recent methods have considered incorporating the two kinds of information, and believe that the combination of the two levels of features is beneficial in annotating images. In this paper, we provide a survey on automatic image annotation techniques according to one aspect: feature extraction, and, in order to complement existing surveys in literature, we focus on the emerging image annotation methods: hybrid methods that combine both global and local features for image representation

Ontology-based semantic classification of satellite images: Case of major disasters

The International Charter 'Space and Major Disasters' is regularly activated during a catastrophic event and offers rescue teams comprehensive damage maps. Most of these maps are built by means of satellite image manual processing, which is often complex and demanding in terms of time and energy. Automatic processing supplies prompt treatment. Nevertheless, it usually presents a semantic gap handicap. The exploitation of ontologies to bridge the semantic gap has been widely recommended due to their quality of knowledge representation, expression, and discovery. In this work, we present an ontology-based semantic hierarchical classification method to undertake this problem. Ontology components are translated to image-based parameters and exploited to assist the classification process at two levels, and using 12 classes. The region of interest is selected from the first level and exhaustively analyzed and classified at the second level. The 2010 Haiti earthquake was selected as study area for this work. Experiments were performed using very high resolution multi-temporal QuickBird imagery and eCognition software

Efficient Implementation on Low-Cost SoC-FPGAs of TLSv1.2 Protocol with ECC_AES Support for Secure IoT Coordinators

Security management for IoT applications is a critical research field, especially when taking into account the performance variation over the very different IoT devices. In this paper, we present high-performance client/server coordinators on low-cost SoC-FPGA devices for secure IoT data collection. Security is ensured by using the Transport Layer Security (TLS) protocol based on the TLS_ECDHE_ECDSA_WITH_AES_128_CBC_SHA256 cipher suite. The hardware architecture of the proposed coordinators is based on SW/HW co-design, implementing within the hardware accelerator core Elliptic Curve Scalar Multiplication (ECSM), which is the core operation of Elliptic Curve Cryptosystems (ECC). Meanwhile, the control of the overall TLS scheme is performed in software by an ARM Cortex-A9 microprocessor. In fact, the implementation of the ECC accelerator core around an ARM microprocessor allows not only the improvement of ECSM execution but also the performance enhancement of the overall cryptosystem. The integration of the ARM processor enables to exploit the possibility of embedded Linux features for high system flexibility. As a result, the proposed ECC accelerator requires limited area, with only 3395 LUTs on the Zynq device used to perform high-speed, 233-bit ECSMs in 413 µs, with a 50 MHz clock. Moreover, the generation of a 384-bit TLS handshake secret key between client and server coordinators requires 67.5 ms on a low cost Zynq 7Z007S device

Apport de l'imagerie satellitale multi-résolution pour l'étude de la dynamique urbaine (le cas d'une ville en zone de transition montagne-plaine)

La présente thèse porte sur l'apport de l'imagerie satellitale multi-résolution à la compréhension de la dynamique urbaine en zone de transition montagne-plaine ; le complexe urbain de Blida est pris comme zone d'étude. Le processus de détection des changements a été réalisé en plusieurs étapes dont : l'extraction de l'emprise urbaine et des réseaux routiers ; l'analyse de l'espace urbain par fusion d'informations spectrale et texturale ; le suivi de la dynamisue urbaine et péri-urbaine par intégration d'images multidates.The present thesis relates to the contribution of the multi-resolution satellitale imagery to comprehension of urban dynamics in zone of transition mountain-plain ; the urban complex of Blida is taken as zone of study. The process of detection of the changes was carried out in several steps of which : the extraction of the urban morphology and the roads networks ; the analysis of the urban space by fusion of spectral and textural information ; the follow up of it urban and peri-urban dynamics by integration of temporal images.PARIS12-CRETEIL BU Multidisc. (940282102) / SudocSudocAlgeriaFranceDZF

Warehousing and analysing textual data

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Use of topographic information to improve a land cover classification. Preliminary Results

International audienceIn this paper, we propose a scheme for a land cover classification process from satellite images, with inclusion of topographic effects (elevation) available from a digital elevation model. First, we study and analyse errors provided from the relief on an available non-topographic classification image. We then present a classification process which takes into account, for each land cover type, the non-unicity of reflectance values according to the elevation. We build a new topographic classification, whose results and their analysis are presente

Tlabel : A new OLAP aggregation operator in text cubes

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TLabel: Nouvel opérateur d'agrégation par catégorisation dans les cubes de textes

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On-Line Analytical Processing on Graphs Generated from Social Network Data

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A Process for Assisting Privacy-by-Design Software Engineering

International audienceToday, the mine vast troves of personal data contained in applications raises the issue of user privacy. Indeed, privacy is increasingly threatened by the spread of unethical practices by device and service providers. Despite the existence of privacy preservation standards such as the European General Data Protection Regulation (GDPR), effective since 2018, there is no widely adopted architectural solution for modeling and assessing privacy by design (PbD) of personal data, as proposed in the various principles of the GDPR. This article presents PRIvacy Assessment Model (PRIAM), which is an approach composedof a GDPR metamodel tooled with a Domain Specification Language and supports a process to protect personal data. The metamodel can be instantiated by architects and integrated in the design of their system, with minimum additional efforts to ensure compliance