LEADER 02717 am 2200649 n 450 001 9910311947903321 005 20181206 010 $a979-1-03-440496-4 024 7 $a10.4000/books.pus.2544 035 $a(CKB)4100000007702291 035 $a(FrMaCLE)OB-pus-2544 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/47926 035 $a(PPN)234838116 035 $a(EXLCZ)994100000007702291 100 $a20190226j|||||||| ||| 0 101 0 $afre 135 $auu||||||m|||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 14$aLes Formes du politique /$fCorinne Grenouillet, Éléonore Reverzy 210 $aStrasbourg $cPresses universitaires de Strasbourg$d2018 215 $a1 online resource (190 p.) 311 $a2-86820-411-2 330 $aLes manières dont le politique informe l??uvre, lui donne sa structure, lui confère sa densité, sont analysées ici en une suite d?études qui montrent aussi comme l?homme de pouvoir qu?est l?auteur sait jouer et faire jouer la littérature à son service : parler de politique, n?est-ce pas bien souvent parler du pouvoir que l?écrivain exerce sur son lecteur, de l?autorité de son verbe ou des fictions qu?il élabore ? Les actes du séminaire réunis ici donnent à voir la variété des formes du politique - l?éloquence, le genre du roman politique, les discours philosophiques et théoriques - ainsi que les postures des écrivains à une époque où se pose nécessairement la question de leur engagement. 606 $aLiterary Theory & Criticism 606 $aXIXe siècle 606 $apolitique 606 $alittérature 606 $aXXe siècle 610 $apolitique 610 $aXXe siècle 610 $alittérature 610 $aXIXe siècle 615 4$aLiterary Theory & Criticism 615 4$aXIXe siècle 615 4$apolitique 615 4$alittérature 615 4$aXXe siècle 700 $aDupart$b Dominique$01290837 701 $aFonkoua$b Romuald$0532248 701 $aGrenouillet$b Corinne$01281586 701 $aLahanque$b Reynald$01302462 701 $aMarquer$b Bertrand$01295942 701 $aPicard$b Timothée$01306556 701 $aReverzy$b Éléonore$0421596 701 $aRey$b Pierre-Louis$0224263 701 $aStein$b Marieke$01316941 701 $aWaller$b Roselyne$01316942 701 $aWittmann$b Jean-Michel$0313088 701 $aGrenouillet$b Corinne$01281586 701 $aReverzy$b Éléonore$0421596 801 0$bFR-FrMaCLE 906 $aBOOK 912 $a9910311947903321 996 $aLes Formes du politique$93032821 997 $aUNINA LEADER 04536nam 2201225z- 450 001 9910566484703321 005 20220506 035 $a(CKB)5680000000037532 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/80994 035 $a(oapen)doab80994 035 $a(EXLCZ)995680000000037532 100 $a20202205d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aMachine Learning in Sensors and Imaging 210 $aBasel$cMDPI - Multidisciplinary Digital Publishing Institute$d2022 215 $a1 online resource (302 p.) 311 08$a3-0365-3753-8 311 08$a3-0365-3754-6 330 $aMachine learning is extending its applications in various fields, such as image processing, the Internet of Things, user interface, big data, manufacturing, management, etc. As data are required to build machine learning networks, sensors are one of the most important technologies. In addition, machine learning networks can contribute to the improvement in sensor performance and the creation of new sensor applications. This Special Issue addresses all types of machine learning applications related to sensors and imaging. It covers computer vision-based control, activity recognition, fuzzy label classification, failure classification, motor temperature estimation, the camera calibration of intelligent vehicles, error detection, color prior model, compressive sensing, wildfire risk assessment, shelf auditing, forest-growing stem volume estimation, road management, image denoising, and touchscreens. 606 $aHistory of engineering & technology$2bicssc 606 $aTechnology: general issues$2bicssc 610 $aactivity recognition 610 $aartificial neural network 610 $aBLDC 610 $aBP artificial neural network 610 $aburr formation 610 $acapacitive 610 $achaotic system 610 $acolor prior model 610 $acompressive sensing 610 $acomputer vision 610 $aconiferous plantations 610 $aconvex optimization 610 $aconvolutional neural network 610 $acut interruption 610 $adeep learning 610 $adisplay 610 $aelectric machine protection 610 $aexplainable artificial intelligence 610 $aextrinsic camera calibration 610 $afiber laser 610 $aforest growing stem volume 610 $afuzzy 610 $aimage classification 610 $aimage denoising 610 $aimage encryption 610 $aimbalanced activities 610 $aintelligent vehicles 610 $alaser cutting 610 $amachine learning 610 $amachine learning-based classification 610 $amarine 610 $amaximum likelihood estimation 610 $amixed Poisson-Gaussian likelihood 610 $amodulation transfer function 610 $aNai?ve bayes 610 $aneural network 610 $anoisy 610 $anon-uniform foundation 610 $aobject detection 610 $aobstacle avoidance 610 $aon-shelf availability 610 $apath planning 610 $apiston error detection 610 $aplaintext related 610 $aplankton 610 $aQ-learning 610 $aquality monitoring 610 $arandom forest 610 $areal-world 610 $ared-edge band 610 $areinforcement learning 610 $arisk assessment 610 $arobot arm 610 $asampling methods 610 $asegmented telescope 610 $asemi-supervised 610 $asemi-supervised learning 610 $aSNR 610 $astar image 610 $astochastic analysis 610 $astructure from motion 610 $astylus 610 $atarget reaching 610 $atemperature estimation 610 $atexture feature 610 $atouchscreen 610 $atransmission-line corridors 610 $avariable selection 610 $avehicle-pavement-foundation interaction 610 $awearable sensors 610 $awildfire 610 $aYOLO algorithm 615 7$aHistory of engineering & technology 615 7$aTechnology: general issues 700 $aNam$b Hyoungsik$4edt$01322435 702 $aNam$b Hyoungsik$4oth 906 $aBOOK 912 $a9910566484703321 996 $aMachine Learning in Sensors and Imaging$93034999 997 $aUNINA