{"id":5176,"date":"2019-05-29T21:47:14","date_gmt":"2019-05-30T01:47:14","guid":{"rendered":"https:\/\/calibercommunications.ca\/analyses-personnalisees\/"},"modified":"2021-10-25T11:21:44","modified_gmt":"2021-10-25T15:21:44","slug":"analyses-personnalisees-2","status":"publish","type":"page","link":"https:\/\/calibercommunications.ca\/fr\/analyses-personnalisees-2\/","title":{"rendered":"Analyses personnalis\u00e9es"},"content":{"rendered":"[vc_row type=\u00a0\u00bbfull_width_background\u00a0\u00bb full_screen_row_position=\u00a0\u00bbmiddle\u00a0\u00bb bg_image=\u00a0\u00bb4312″ bg_position=\u00a0\u00bbcenter center\u00a0\u00bb bg_repeat=\u00a0\u00bbno-repeat\u00a0\u00bb scene_position=\u00a0\u00bbcenter\u00a0\u00bb video_bg=\u00a0\u00bbuse_video\u00a0\u00bb text_color=\u00a0\u00bblight\u00a0\u00bb text_align=\u00a0\u00bbleft\u00a0\u00bb top_padding=\u00a0\u00bb12%\u00a0\u00bb bottom_padding=\u00a0\u00bb12%\u00a0\u00bb enable_gradient=\u00a0\u00bbtrue\u00a0\u00bb color_overlay=\u00a0\u00bb#0a0a0a\u00a0\u00bb gradient_direction=\u00a0\u00bbleft_to_right\u00a0\u00bb overlay_strength=\u00a0\u00bb0.95″ enable_shape_divider=\u00a0\u00bbtrue\u00a0\u00bb shape_divider_color=\u00a0\u00bb#ffffff\u00a0\u00bb shape_divider_position=\u00a0\u00bbbottom\u00a0\u00bb shape_divider_height=\u00a0\u00bb250″ bg_image_animation=\u00a0\u00bbnone\u00a0\u00bb video_mute=\u00a0\u00bbtrue\u00a0\u00bb shape_type=\u00a0\u00bbcurve_opacity\u00a0\u00bb][vc_column column_padding=\u00a0\u00bbno-extra-padding\u00a0\u00bb column_padding_position=\u00a0\u00bball\u00a0\u00bb background_color_opacity=\u00a0\u00bb1″ background_hover_color_opacity=\u00a0\u00bb1″ column_link_target=\u00a0\u00bb_self\u00a0\u00bb column_shadow=\u00a0\u00bbnone\u00a0\u00bb column_border_radius=\u00a0\u00bbnone\u00a0\u00bb width=\u00a0\u00bb1\/6″ tablet_width_inherit=\u00a0\u00bbdefault\u00a0\u00bb tablet_text_alignment=\u00a0\u00bbdefault\u00a0\u00bb phone_text_alignment=\u00a0\u00bbdefault\u00a0\u00bb column_border_width=\u00a0\u00bbnone\u00a0\u00bb column_border_style=\u00a0\u00bbsolid\u00a0\u00bb bg_image_animation=\u00a0\u00bbnone\u00a0\u00bb][\/vc_column][vc_column centered_text=\u00a0\u00bbtrue\u00a0\u00bb column_padding=\u00a0\u00bbpadding-1-percent\u00a0\u00bb column_padding_position=\u00a0\u00bball\u00a0\u00bb background_color_opacity=\u00a0\u00bb1″ background_hover_color_opacity=\u00a0\u00bb1″ column_link_target=\u00a0\u00bb_self\u00a0\u00bb column_shadow=\u00a0\u00bbnone\u00a0\u00bb column_border_radius=\u00a0\u00bbnone\u00a0\u00bb width=\u00a0\u00bb2\/3″ tablet_width_inherit=\u00a0\u00bbdefault\u00a0\u00bb tablet_text_alignment=\u00a0\u00bbdefault\u00a0\u00bb phone_text_alignment=\u00a0\u00bbdefault\u00a0\u00bb column_border_width=\u00a0\u00bbnone\u00a0\u00bb column_border_style=\u00a0\u00bbsolid\u00a0\u00bb bg_image_animation=\u00a0\u00bbnone\u00a0\u00bb][vc_column_text css_animation=\u00a0\u00bbfadeInUp\u00a0\u00bb css=\u00a0\u00bb.vc_custom_1557935609354{margin-bottom: 15px !important;}\u00a0\u00bb]\n
Analyses centralis\u00e9es pour \u00e9voluer avec votre entreprise<\/h5>\n[\/vc_column_text][split_line_heading]\n

Analyses personnalis\u00e9es<\/h1>\n[\/split_line_heading][\/vc_column][vc_column column_padding=\u00a0\u00bbno-extra-padding\u00a0\u00bb column_padding_position=\u00a0\u00bball\u00a0\u00bb background_color_opacity=\u00a0\u00bb1″ background_hover_color_opacity=\u00a0\u00bb1″ column_link_target=\u00a0\u00bb_self\u00a0\u00bb column_shadow=\u00a0\u00bbnone\u00a0\u00bb column_border_radius=\u00a0\u00bbnone\u00a0\u00bb width=\u00a0\u00bb1\/6″ tablet_width_inherit=\u00a0\u00bbdefault\u00a0\u00bb tablet_text_alignment=\u00a0\u00bbdefault\u00a0\u00bb phone_text_alignment=\u00a0\u00bbdefault\u00a0\u00bb column_border_width=\u00a0\u00bbnone\u00a0\u00bb column_border_style=\u00a0\u00bbsolid\u00a0\u00bb bg_image_animation=\u00a0\u00bbnone\u00a0\u00bb][\/vc_column][\/vc_row][vc_row type=\u00a0\u00bbfull_width_background\u00a0\u00bb full_screen_row_position=\u00a0\u00bbmiddle\u00a0\u00bb equal_height=\u00a0\u00bbyes\u00a0\u00bb content_placement=\u00a0\u00bbtop\u00a0\u00bb bg_color=\u00a0\u00bb#ffffff\u00a0\u00bb scene_position=\u00a0\u00bbcenter\u00a0\u00bb text_color=\u00a0\u00bbdark\u00a0\u00bb text_align=\u00a0\u00bbleft\u00a0\u00bb top_padding=\u00a0\u00bb5%\u00a0\u00bb bottom_padding=\u00a0\u00bb2%\u00a0\u00bb overlay_strength=\u00a0\u00bb1″ shape_divider_color=\u00a0\u00bb#f2f2f2″ shape_divider_position=\u00a0\u00bbbottom\u00a0\u00bb shape_divider_height=\u00a0\u00bb200″ bg_image_animation=\u00a0\u00bbnone\u00a0\u00bb shape_type=\u00a0\u00bbcurve_opacity\u00a0\u00bb][vc_column column_padding=\u00a0\u00bbno-extra-padding\u00a0\u00bb column_padding_position=\u00a0\u00bball\u00a0\u00bb background_color_opacity=\u00a0\u00bb1″ background_hover_color_opacity=\u00a0\u00bb1″ column_link_target=\u00a0\u00bb_self\u00a0\u00bb column_shadow=\u00a0\u00bbnone\u00a0\u00bb column_border_radius=\u00a0\u00bbnone\u00a0\u00bb width=\u00a0\u00bb1\/4″ tablet_width_inherit=\u00a0\u00bbdefault\u00a0\u00bb tablet_text_alignment=\u00a0\u00bbdefault\u00a0\u00bb phone_text_alignment=\u00a0\u00bbdefault\u00a0\u00bb column_border_width=\u00a0\u00bbnone\u00a0\u00bb column_border_style=\u00a0\u00bbsolid\u00a0\u00bb bg_image_animation=\u00a0\u00bbnone\u00a0\u00bb][vc_widget_sidebar sidebar_id=\u00a0\u00bbtechnology\u00a0\u00bb][\/vc_column][vc_column column_padding=\u00a0\u00bbno-extra-padding\u00a0\u00bb column_padding_position=\u00a0\u00bball\u00a0\u00bb background_color_opacity=\u00a0\u00bb1″ background_hover_color_opacity=\u00a0\u00bb1″ column_link_target=\u00a0\u00bb_self\u00a0\u00bb column_shadow=\u00a0\u00bbnone\u00a0\u00bb column_border_radius=\u00a0\u00bbnone\u00a0\u00bb width=\u00a0\u00bb3\/4″ tablet_width_inherit=\u00a0\u00bbdefault\u00a0\u00bb tablet_text_alignment=\u00a0\u00bbdefault\u00a0\u00bb phone_text_alignment=\u00a0\u00bbdefault\u00a0\u00bb column_border_width=\u00a0\u00bbnone\u00a0\u00bb column_border_style=\u00a0\u00bbsolid\u00a0\u00bb bg_image_animation=\u00a0\u00bbnone\u00a0\u00bb][split_line_heading]\n

Plus d\u2019objets, plus pr\u00e9cis<\/h1>\n[\/split_line_heading][vc_column_text css_animation=\u00a0\u00bbbottom-to-top\u00a0\u00bb css=\u00a0\u00bb.vc_custom_1557935515783{padding-right: 10% !important;}\u00a0\u00bb]Caliber Communications a d\u00e9velopp\u00e9 son propre r\u00e9seau neuronal pour faciliter l\u2019int\u00e9gration des formes d\u2019analyse avanc\u00e9es et d\u2019intelligence g\u00e9n\u00e9rale. Cette technologie traite un large \u00e9ventail de hardware et de logiciel internes pour fournir une grande quantit\u00e9 de puissance de traitement et permet de faire les d\u00e9terminations avanc\u00e9es.\u00a0<\/span><\/p>\n

Les syst\u00e8mes de Caliber utilisent une multitude de proc\u00e9d\u00e9s o\u00f9 chaque se rapporte \u00e0 une t\u00e2che sp\u00e9cifique dans un flux vid\u00e9o ou dans une image. La base de donn\u00e9es d\u2019actifs, le syst\u00e8me primaire de Caliber, abrite toutes les images utilis\u00e9es pour la formation d\u2019intelligence artificielle sous une forme math\u00e9matique. Comme tous les objets suivent un mod\u00e8le math\u00e9matique, un algorithme qui tombe dans une zone de flou d\u2019une correspondance peut d\u00e9terminer qu\u2019un objet a \u00e9t\u00e9 d\u00e9tect\u00e9.\u00a0<\/span>La formation approfondie du syst\u00e8me I.A. est faite pour d\u00e9tecter les ressemblances math\u00e9matiques entre les variations d\u2019un objet afin de faire ces d\u00e9terminations par programme.\u00a0<\/span><\/p>\n

Alors que les flux vid\u00e9os sont surveill\u00e9s par le syst\u00e8me I.A., la vitesse de traitement est vers le haut de 70 trames par seconde. Lorsque les correspondances sont faites, le syst\u00e8me va utiliser en continu les algorithmes pour d\u00e9terminer si le niveau de confiance monte ou tombe. Si le niveau de confiance monte, une identit\u00e9 positive est faite. Si le niveau de confiance tombe, c\u2019est d\u00e9termin\u00e9 un positif faux et ni\u00e9. Normalement, l\u2019analyse de la cam\u00e9ra requiert un segment de vid\u00e9o pour faire une d\u00e9termination; le niveau de confiance ne peut pas \u00eatre confirm\u00e9 ni refus\u00e9. Cette restriction est \u00e0 cause des ressources du syst\u00e8me faibles, peu d\u2019espace du disque dur et une puissance de traitement faible.\u00a0<\/span><\/p>\n

En centralisant ces programmes sans restriction d\u2019acc\u00e8s aux flux vid\u00e9os, Caliber est en mesure de traiter chaque trame de vid\u00e9o ind\u00e9pendamment, ce qui donne 30 d\u00e9terminations qualifi\u00e9es pour une seule seconde de 30 images par seconde de vid\u00e9o, ce qui augmente le niveau de confiance et assurant une identification positive est compos\u00e9e au cours d\u2019une ou plusieurs secondes.<\/p>\n

c.-\u00e0-d. si une identification positive d\u2019un objet est faite 60 fois de suite sur une p\u00e9riode de temps de 2 secondes avec un niveau de confiance de 80 pour cent – \u00e0 l\u2019aide d\u2019un logarithme, on peut d\u00e9duire que le niveau de confiance total pour les 2 secondes augmenterait \u00e0 99.999 pour cent.\u00a0<\/span><\/p>\n

En plus de maintenir des taux parfaits de d\u00e9tection sur les objets analys\u00e9s, Caliber est en mesure d\u2019entra\u00eener le syst\u00e8me I.A. \u00e0 d\u00e9tecter beaucoup plus d\u2019objets. Typiquement, les fabricants de cam\u00e9ras avanc\u00e9es actuels sont capables d\u2019employer les analyses qui peuvent d\u00e9tecter les personnes, les v\u00e9hicules, les franchissements de ligne et les d\u00e9tections d\u2019intrusion. Bien que ces analyses semblent avanc\u00e9es, elles sont incapables de comparer contre une multitude de variations sur les objets et donc produisent les fausse positives ou n\u2019identifient pas du tout. Les points suivants vont mieux expliquer pourquoi ces analyses sont limit\u00e9es:\u00a0<\/span><\/p>\n

Une cam\u00e9ra de haute gamme typique peut incorporer environ 50 megs dans une m\u00e9moire r\u00e9manente qui est utilis\u00e9e pour stocker les algorithmes que la cam\u00e9ra peut faire la r\u00e9f\u00e9rence\u00a0<\/span>crois\u00e9e pour la d\u00e9tection. Cette base de microdonn\u00e9es dans la cam\u00e9ra va ensuite utiliser un CPU \u00e0 base ARM (machine RISC avanc\u00e9e) pour traiter les images contre la base de donn\u00e9es \u00e0 330 m\u00e9gahertz, d\u2019habitude. En comparaison, la base de donn\u00e9es centrale de Caliber comprend un r\u00e9seau neuronal qui est 100 gigaoctets de taille couvrant toutes les correspondances possibles pour plus de 4000 objets. 100 gigaoctets sont 800 fois plus grand que ce que la cam\u00e9ra peut faciliter pour les comparaisons; la puissance de traitement de Caliber est actuellement 16,000 fois plus rapide que ce qu\u2019une cam\u00e9ra peut produire. \u00c9videmment, ceci m\u00e8nera \u00e0 une base de donn\u00e9es comparative plus grande et beaucoup moins fausse positives du syst\u00e8me.<\/p>\n

En centralisant le syst\u00e8me de d\u00e9tection, il n\u2019y a aucune obligation de mettre \u00e0 jour les cam\u00e9ras ou les syst\u00e8mes dans le domaine pour profiter de d\u00e9tections nouvelles faites dans le syst\u00e8me de Caliber. Par exemple, Caliber a form\u00e9 r\u00e9cemment le r\u00e9seau neuronal de Caliber de d\u00e9tecter les bobines de fer de tailles et types variants aux fins de l\u2019inventaire des objets sur les sites du client et pour assurer que les personnes qui s\u2019approchent ces objets d\u00e9clenchent le syst\u00e8me \u00e0 suivre une multitude de logique incorpor\u00e9e dans syncroReports. Une fois la formation personnalis\u00e9e est termin\u00e9e pour un type de d\u00e9tection, elle peut \u00eatre activ\u00e9e imm\u00e9diatement et \u00e0 distance sans avoir besoin d’appels de service ou de mises \u00e0 niveau mat\u00e9rielles pour que tous nos clients puissent en b\u00e9n\u00e9ficier.\u00a0<\/span>[\/vc_column_text][\/vc_column][\/vc_row]\n","protected":false},"excerpt":{"rendered":"

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