{"id":55262,"date":"2024-04-15T17:41:24","date_gmt":"2024-04-15T16:41:24","guid":{"rendered":"https:\/\/presse-express.dz\/?p=55262"},"modified":"2024-08-07T09:06:48","modified_gmt":"2024-08-07T08:06:48","slug":"ai-finder-find-objects-in-images-and-videos-of","status":"publish","type":"post","link":"https:\/\/presse-express.dz\/?p=55262","title":{"rendered":"AI Finder Find Objects in Images and Videos of Influencers"},"content":{"rendered":"<p><h1>What is Image Recognition their functions, algorithm<\/h1>\n<\/p>\n<p><img decoding=\"async\" class='wp-post-image' style='display: block;margin-left:auto;margin-right:auto;' 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\" width=\"306px\" alt=\"ai based image recognition\"\/><\/p>\n<p><p>In this article, we are going to look at two simple use cases of image recognition with one of the frameworks of deep learning. Visive&#8217;s Image Recognition is driven by AI and can automatically recognize the position, people, objects and actions in the image. Image recognition can identify the content in the image and provide related keywords, descriptions, and can also search for similar  images. We are going to implement the program in Colab as we need a lot of processing power and Google Colab provides free GPUs.The overall structure of the neural network we are going to use can be seen in this image. Numerous image recognition programs are far better, quicker, and more accurate than their human counterparts.<\/p>\n<\/p>\n<p><img decoding=\"async\" class='aligncenter' style='display: block;margin-left:auto;margin-right:auto;' src=\"https:\/\/www.metadialog.com\/wp-content\/uploads\/feed_images\/future-of-customer-support-top-5-trends-img-3.webp\" width=\"305px\" alt=\"ai based image recognition\"\/><\/p>\n<p><p>Bag of Features models like Scale Invariant Feature Transformation (SIFT) does pixel-by-pixel matching between a sample image and its reference image. The trained model then tries to pixel match the <a href=\"https:\/\/www.metadialog.com\/blog\/ai-in-image-recognition\/\">features from<\/a> the image set to various parts of the target image to see if matches are found. Some of the massive publicly available databases include Pascal VOC and ImageNet. They contain millions of labeled images describing the objects present in the pictures\u2014everything from sports and pizzas to  mountains and cats. Returning to the example of the image of a road, it can have tags like &#8216;vehicles,&#8217; &#8216;trees,&#8217; &#8216;human,&#8217; etc.<\/p>\n<\/p>\n<p><h2>AI Image Recognition Tool<\/h2>\n<\/p>\n<p><p>The technology uses artificial intelligence and machine learning algorithms to learn patterns and features in images to identify them accurately. The system trains itself using neural networks, which are the key to deep learning and, in a simplified form, mimic the structure of our  artificial brain tries to recognize patterns in the data to decipher what is seen in the images. The algorithm reviews these data sets and learns what an image of a particular object looks like.<\/p>\n<\/p>\n<p><img decoding=\"async\" class='aligncenter' style='display: block;margin-left:auto;margin-right:auto;' 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width=\"309px\" alt=\"ai based image recognition\"\/><\/p>\n<p><p>AI image recognition enables healthcare providers to amplify image processing capacity and helps doctors improve the accuracy of diagnostics. As digital images gain more and more importance in fintech, ML-based image recognition is starting to penetrate the financial sector as well. Face recognition is becoming a must-have security feature utilized in fintech apps, ATMs, and on-premise by major banks with branches all over the world.<\/p>\n<\/p>\n<p><h2>Image Recognition compared with other terms<\/h2>\n<\/p>\n<p><p>As an offshoot of AI and Computer Vision, image recognition combines deep learning techniques to power many real-world use cases. Whether you\u2019re manufacturing fidget toys or selling vintage clothing, image classification software can help you improve the accuracy and efficiency of your processes. Join a demo today to find out how Levity can help you get one step ahead of the competition. Images\u2014including pictures and videos\u2014account for a major portion of worldwide data generation. To interpret and organize this data, we turn to AI-powered image classification. Image recognition is a subset of computer vision, which is a broader field of artificial intelligence that trains computers to see, interpret and understand visual information from images or videos.<\/p>\n<\/p>\n<p><a href=\"https:\/\/www.metadialog.com\/\"><\/p>\n<figure><img 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im7DQeONL2zi2vtIhEqSebdlraLepypO\/AYg9gCfag6iYc3HRDGUaVMutqwDiMhxnlAwTII5cyMGcRpNTS0i4iHFltKkljJpM10JTH5Us0vlNF5kkfRDJMwPy5UgnBOCaxGqxNBY6cHK58kllB5gsxcZHb5WX862WpIb9J7a5mku5LmVZbq42eUZ5FGQipyEcSjIVcLyO4gBVA55f3E1xeTzXC7ZGc5X+Hnjb9B0+1NrEBTcIpl0Sf2gDyEx3d55DlgHAbZqQWpDPSGaq0rog1KL+lP6aQ2pWqkkZmQcjz61EJ9KElaJ1kRiGUhgfQik1QU5zNTSFqCSeCb3GfM8+3LeuzfPu\/xGL9K1kV1qWi8H6trnDLSJqqQaPaSzw5822s3s0dnUjmuZNgz7+oBGS4bmiktpbHViRFf7kRUx5siuRuKL0JDIjKDgEqVHXlohd3HDN9FxDoj68+22gs5J7OOKS0l8qJI9rBg4Odmdkiggnpyq0w+6HDw6jfPquYvmFz3UoBJdIB\/a7LDpJ66TOD4HIVhp9\/rercEWF9xXc3FzeRXGpzadNdsWnaFLB2c5bmy7kUZ9VA6BcZDRHa04ciuHU7YzezgnodyxKg+5hk\/7av8A4681fVm13iGz1qJ7izuraKW9uI0Xy5YHjbyYFhXIAckBdqA82IGTWb4qvfJsobOGARRyKI0ReSxxqFIH9ZjyJY4ySx\/f5JUdpbrPL4nb7JLKiTU7ENA1GSBGkZfIEdD0zJgTCz8kWmySP8Pdyxpn5BNFnl7lSef2p2DSJrgF7S5tZ8dVWYK\/2V8MfsDVcelORfirPpkOdkLqnMeG+6745+3zVtDYXUP9NbSpg4+ZCKs7W2yOntUXSpr3zUgtJpQzkBVVyATXTdB0ma5a2s3dpp52KRCOMGWZwMkIOWfdiRgDmf3a0KdPXsue4nfG0EvhZC30i5nISOBskcs\/KD9zUO7sXhZo5YyjDqGGCK6eEtPKl+IAgSJcu8d1DM0YyBkqmGIyRnBJ9jVBxHZxSQuj7TMiCWMpz3KcYIx1U5HTueg5ipXUYEhY9txV1SrpcMfFc3u4AM1Uzrgmr2961S3GM1TeMLsLVxIUaiiiqCvoooopEIooooQiiiihCKKKKEIorzI9aKEK4Dn1r0SY7VGD+9eh8dDWhKoGmpO8HvSg+T1qMHPegP60spvZqVux3\/Wn7G9eyu4btRkxOHx64PSoHmD1NG8etKDCY6kHAgrb6BfnSNTFvGA8M5Nxao7cpopFKyQk+rxkp\/aUVVa7ozaJdR3lsfitNuG32s+OTAHnG4\/ddejKe49MGoFjqNvJb\/zZqTMIAxeGVRloHPUgd1OBkfcc+ur0zULm2g8u8v7WUXg2ktteG6C9C6vhHYZHPKSD3qdpDxpWLVZUtKvajM4I7x3g94yT57yCJV1w6Nc44fWbm2urrQtYuZbxLq2R5FAk3MqOY1coQxCsNpIwSAeWfOPLLT9Is7Pg3RJJrqVr6W+WDm5t\/MihTyxlVYlmRjzVTtWMkAkgQZzFZzFYeDL1w4zvsZ7iKNvbBDZ+xxUd9R1KxhkS1sbHhtZlKyTF2N26nqAWJkAPfaFB6Gnktgjv8f6KjSpVTVpvDjpYIAJAB5AkBzjIB5DPQJVzbLZWsHCEd2pkaUXmqyR\/MkZVSFjz+8UVnzjluYjnio3EGq2xuI9OksgYYCWddxWRWP7obpyUIpyDzWozavpWmac0GmEzSzj5i4GSRn5n5evNUGQOpJOBWeaXcSzEkk5JNRPfGAta2tC92upOJ6Ek7np3Ad0K1Fvp10SLXUDCx6JcrgH23jI\/PFMXVleWa754GCHkHBDIfow5Gq8vz5VYyyNb6DFGpI+MuGdvdUGF\/Vm\/Ko5lXix9MgAyCYz9\/DxV5o0EWtQvNdvDb2Fh8zRlmSGIYHzuRzYseQVcsx5cgKeHF+h6Z+z03S7i6PeSWc20Z\/sxw4Yf3nNLurDSE0NdO1LU7yxtNNW2lnFpZJO891cIXJbdLHgKqqo5nHPlzNUx\/wDh9DzNzxDd+3kwW+f8clTElm0LJYylclxeHETgAOjvB1YyQZ355yrm34s0PUblDcxT6ZPuAErStcQfcn9qn1Vm+lS9QsjLE1hcgjymMi7ZFkCHG4SLj5WBX5sjk6g8gy88yb\/gBenDuvP7trEK\/oLY\/wCdahWsWiNhbRSxpYx2sts8sgklEc9uJ1iZgFDBJhy5DlI4pzXaxBIP54KG4ofp3B1NjmjfJB7hI94nc7HvxEZo4tcikuTp2txQwSW2U83qgKnptKPj227RUibWdDsyLlLyGeYY2iNDke+din8nFZ\/imWF9SzGw8xFMMoHrGxRSfcoqmqUt71AapaYWtS4dSrtbUyJ3A2V5q3Ekt8htbVTFAQQxONz5OT05AE9h17k1En239j8WgUT2yhJ1AxvTosmPbkp+x7k1W5NXHD+mXcsyX25IrcbgxcZEi9GGCRywcEkgDPXOKYHF5hXHUqVpT1NxHr08\/wA2VPupORWlm4Xsgx8zUPhlLMUU7SxQn5ch2Q9O4GDSzwtp8luFhuGZ\/wAKzxsrKzfwlQSuT6B8+imkNJ6P8RtxGfT89FliamRww2US3V6gd3GYYM9fRm9F9up+lKkgj0iVvPMNxcD+iVWDIvP8TD1\/qn7+hgSyyzyNNNIzu5yzMckmq7jo33Vsf6237fn4JwXOZmnmjWVmBwDyAPY4HLke3StTpXE8Dyvdy3g0y6wA0iPJ+0+hRS\/bu59qyFFIyu+mZCZcWlK5bpd+fT0Wsv8AiOwhaR7aZryeUgySFThwDnBZlVvzDH0I61SXdzLrMb3MrqLiAE+Wq4DRkkkj3BJz3IOexqurXcN6MkUUN4nO5kQurn5BGMZJBYqAAOZYkDn+JRgtI1z7l2k7KrUp0eHU9Y37\/wA2CzUel6lKoeOwuGUjIIjOCKaCvFIY5FKspwQRgg+la281TSNxhTX\/AId92d9rZecGP9d2Kbvrtb6mmfh4kRZL6OxurK+bykvrZPLXzRz2OMDy3weu0dcncM07sGtPun5fRDb58S9sTygg+og45AyjhPTpr7U7KNGTM7lU3dAcgAt7ZYZ+9dH8K9XXUfFSz1AM3wtmlw0YY81iEThc+5LZPuTWH4bMeia3p8d\/IUgG7dJj\/wCnvRy31Cc8e2KtfDnia\/8ADvWde1ZtOt7i803TpbfybgEx73niiJ5dcBmI+lXqLgwtJ78+S53jNJ97QrtpiXOZpbynUS3f4Z5ea90u7T4TWZWb\/wDChR9TMlO2V68ltpk27LRTTwL\/AGAFcD6bmP5mqwcR3eo6BqiSWthEm+BF+HsoomLFyQNyqGPJTyJpq7vDolvCm5TPYglweYFzIQSn91FGfRuVIHACR+ZSm1c5zmuHvatt\/wCQDuHePiqHUpFWeREPJXIH0zVNO2Tmnp7gsTzqIzZNUqr4C6u3paG5XlFFFUlaRRRRQhFFFS9N0nVNYn+G0vT7i6lxkrFGWwPU46D3PKnBpOya5waJcYCiUVqOJ\/D7XuC4opuII4gtzGjwPbSrPEzMA20yISgYA8wCSD2rMgelSGkWmHBRUbilcM7Si4OaeYMhJxXu00rb60oLTgxSkpvb70U7tNFO7NJqSg3fNe7\/AHprd7UZFO1JulPb69EmfWmQfevdx9aXUk0J\/f7Ub\/amNxo3Gl1BN0J\/zPpXu8VH3etLhR55UhiUl5GCqPUk4FEoLYyVc3kzWmk2FoCqvKHuWIUBgrHaqkjmfwlv7wqqMmTkkfen9Znjl1KYRNujiIhQjoVQBQfyFQd1Oc7KhoU4YCdzn45T+\/2rzf6AUzuNG40moKfQnTJj1rRBluuDisZG+3YOw74WQg\/\/ALy\/lWYyfWrzhm\/hWR9MugGjuPwZbA3EEFcnpuUkezBT2p1NwmO9VL2mezDx\/KQfgtXfaPq+v2usNo+nT3b3kemXqJChY7DGyk8uwbK\/as3FwDxdNMbddKAlCljG9xErAAZJILA8hVhHpYu9LOiatMfLtXLafeLEWeJGOWR0HzFM5JAyyNk4IbnO0HWPFfga2aw4QuW+HeRpRc6YsdwGJAB\/aICRyA+VsEc+Q51YIa4guB8vssRlW4t6bmWr2asQHyAQAADqBPICRpkHpBOcn4N1u1leG9fTraRGKssuowKQQcEfj9a1qwLAkl688Mkc8dlbQtFIHDyW9oqPgjkR5zxJkcid3oag603GPGNzb3\/iNxBLM1sCkUDOj3RUnLDaOUQ\/rSbR9ele6hfWtlCboxx28MKCKKOMs2yME7Y1LY5nLHd1JdpCANgI0NZJEx13SVate5axtQtLtjokt3Bw45OQOWMhZTiSBYdWmYSbmnzcMP4Q5LKP+0qfvVTuqQZpL67nnlOXkWSRvrgmomTVB78yF01BhYwMduAE9BBLdXEdtCN0krhFHqScCt3cXdppOnC7vXLomI4o422PO4AOBj8ChSCSOahlUfMWYZ\/haBFVrppirTTLaou7AbeQrcu5AfI+hrdWGovp9peyRGRBZrp0p8qVoncyWF5dyLvXDAGUjOCDhV9BVq3bDZJ3WHxa49\/SGyG75icgHPmPXIWBl4r4mvpfLsLmW1Qn5LewUxqPsvNj7sST3Jq90604z1eJrXiDhjXL2zkXDX0dhIbi3Xu3mBcug6lGJGBy2nnSLvxc4huYvK+H2qP4tU1GT8w9yV\/StrwbbaVqulafxJNYWg1FPiZrlvh5mb5SvkFGwUXG2Xdlgfw56iiiBVfAeT8lV4hcPsqAqPtwzMCIcZgmZERtvnJzuuXavZX0glinAkutOkMM7J0kTBKye\/Jfxdxs71SDnzFbdipufMlwHfh22M\/2MYX7+WENY+1gMsFw4H9Gm41VrUwXCOc+i3bKuXMIdyj138p26Jiiiiqq0VbcN2Md5euZo1kSKNjtboeRz+ShiPcCrjXp7iSey4dtl8s35iklx+J1c\/sVPopUrJtHL5wP3VxTaHcyWwYocB7iBXP9Qls1p4rQyeJPC0jDfFeT6VsI5ggCFGX+6ysv1U1fpD\/R93ckepWJdu0XJe\/ZrSR4gA\/WfKVvrLQOMbvw64r1qz0zUku4b6SKxgg0yZZEj8+2KujIAioIzOMYyck\/u1zvWIJG454m4buWfBN3A278XnWysyMf6xaLBPo7etbTRbvXZ+MtO0vU9S1W50+No7WW0fSi8bR+WFaNmb8QPMc6xQlfUOOOI9eiyY3ub3azes7SLnPqEZ3\/ALlWq0O0gTvB8pn5rneFtq0albWWmW6hAIgu0hrZMTBZPiVBvLlN1hMZfKnaFZIJWb5UkwrMGB5bWZmzn1HbNafTryZ1LHT1W8eBYZ1SKKZ2jBDIGWRHRgMDDHY2ABlhg1kOMpFN9bxIpXZboWz64xn7gA\/eqie6uzClnLcSNDGAyIzZCZGeWenXtVY1+ycV0H6EXlFh28c8\/Xw78+PSJ9XWyX4e6uRExYSIsoijMbAEB1jRFUNgkA\/NjJ5qfmHPtS1H4mQRxgrDGSEBbcSSebMe5PrUCioqt0agiFbs+G07QlwyT0helia8ooqqSTutFFFFXvCvC9zxFLcTGVLWxsk3XN5MreVCSDsDFQcE4OB3we2SHMYXu0hR1qzKDDUqGAFRVq9E8M+J9XiS8uIodKsmQS\/E6gxjHl5xvWNQ0rrkjmiN1qdHc2mhMI+GNOhuZ5Jj8JOE865nReYcd4wTj8IVhtI65x2fwk4Q4t1jS9ZvNW4B0mXVNQi\/YXXFJlaO1UsnOG2XmzEln3SAD5OrHFWmWpcYAk9PusO\/47Ss6fa1nNpM73nP\/UGfyN8LkllB4c8NXLT2+l3XFE1htM02qBrSw8w\/hXyUbzXHInnIuQD8p6Ve6VceJfHeg3jcM8FStpDXSWz3emWTRQwykErGFj+SNT1+UZ7sWrr3DP8AJt4A0i\/sbbjviWbWby7u40jtQGito97qGKxIc9CcEkL0GK7hqV\/wlwRpH\/CvAqWVho8N\/aW08NptVDMz7WeQD95QW5nn8prVocNcBLiB6lebca\/iPZCoKNlRfXc7ZxlrBBwY3OeUDxxK+QeL70adwLZcLajNLfSaZpMj3Ec0qyJaXcsgSNQQAGwmGXOceYSDyGOKBa6j4mcQx+VeJooW2t+I7hpbqFUAHlQSMtugGPlVUCjljJDVzQIB2qncQ53gvQvZuk6jaF7hBc4nzP7scve1RvIgnMpsJ3FKCfenVjzS1T1qEBbpemPL9qKk7B\/DRSputVWa93GvKKoalche7q93Ck0U4ORCVu96kWVld6hIYrSMuVUu5JwqKOrMTyA9zTCRSSHCIWIBOAM8hzJrQ6Bpt5rMEdgEK2wk2iKLCvdS82wWPIBV5ljyVRnqec9NpeYVa5rCgwvkDx5fnl4qJZ2OmyqkSC91K7cZ+HtI9qr\/AHiCSfouPerrTNDmEhlXh+SCeP8Ao0meR2zg89qoenXBFF9xDo2htLY6VZ2+puvyFyXWyQ\/+nGCGl\/tyk5\/hrzV+Jr6DSdCuobLSB8Raymdf5pttrutxKMkeXy+TYOWOnrVgdnTmTt3LJqOuq8aGwHGBqJB2J2G2BGRPzUW74VhaKSSxuXjkh\/pYpjuCD1LAAr\/fRR71n7q2ubKdra6iaKROqt+h9wfWtnpWv6fr9xHbLbppl+VKwxrK5tpm7KjOWeBz0GGKE4BABNN6np0eqW3wzL5dwnKLzIvLZZASCmP3csNjL0VypGAxpHU2vbqplOoXtag\/s7gfHceYwR8fiCFis+9G73pJBBwRgiiqWtbkL3cKN1eUUhelhXVtxTew2xglijnbaFDv1IHTd6kDkG5MOx7VbW3EMctnHdahDYAuzIpnQSudoGfmaKRsfN3asfUi4DC1tQWYgozAHoPnI5f9tTMuHgHoqNawoPI92JP0WluuKrCJA1uGnlA+VUjEUUfuO2fcIp96zd9qFzqEgedvlXkiAnag9s\/qTzPeo1GMnAqN9Z9TBUtCzpW+WjPerC2gMdwwI\/FZvIPvETVdWquLIoLaUL+LSpWP2gx\/rWZSJmlMWOYB\/QE\/6U+swggBNtqwqy7oPqp9tefAWtvkHzEuIruP0+UuG\/yX8q3T6zZaZpEmoz6bcXkcjWUcphdAg8m3nhi3hlYbZYJVIOPxI47VltQ0O4kvoLKGLcY7R2bJCgYeTqTyHSndLurzT1aLTZU1CIgoVhG+SME5KGN1xLGeuCpGRn5TmrNMupmFmXdKldtDhnvExInaRttPXrsbJfEjTrdNtlwlZR46GS005yP7wsw\/+KpnDXFusa3qxSC3kit2XZcu93M0UcZDIP2YIRm+dti4\/EfrVUl7wfdTkPw1bR3C\/ijLSwxk98qZ+X0Dr7AVp+GDBdXCwxtDHHFNhbeBdqI+x\/lC92wDlm3E4\/GeYMtLtXOEvkdP7LOvKdpQoPLKBaY3P9zPn67LD69PMrXXmRhHuZEIQNny4EUpEuR2xjl3CqfSjRtPdrLWkK\/NDbg1KsLSfiC2u78whQbi3iUKOg3Y5nuefM\/5DlWv4Z4ekm1Xim1EZ2JGkfTuR\/8A2Kayl2jg7v8A6q5dXzLSg5hwWxPkWD6wuVSxGNIXx\/SIW\/xEf6U3V\/xDpjWOj6PMVx5guYyf7ExH+tUFZ1Vmh0Hp8lu29YV2a295HwJH0T1vcNCk0IQMs6bDnscggj3yPyzXStJLGz0a+vs6bqunX6y2t3tV9su\/ereXJ8kiM2GwD1JIDA7a55olk2oata2i9XcfkOf+ldS0zSJoeC7aS5to50GsxxosoJAVp9owQQR9jV2yaSCeX9lhceq06ehp3JHqCPA7QQcHmod3qvGyXuNR4tisow+VbTNMSzmkPYKwiiBJ\/tHHYGqS8v7TSbNYkQKsZYRwCTexkJ+ZmJAy2duWwD8oAC4ApHG00+ia3c6VY6fBA0yl2dS5Y5yDyLFeg9KzOhWD6jqUNui5+cZ+nX\/Sn1KpD9A36k\/VNsrKk6gLgw1kAwABP\/X+vPZWPE1pO9\/BvBLtZrK3L3aq7XLY2moyQEY2LGP8C\/7107XuGZDrbq0WBHpkGOXq8n+wrG+JGntY8R3qbceXcCM\/UQxH\/Wm3FAtY53X7qThnEmXFSnSaf5Sf\/P3WUooorNXRIooowaUCUIr6M8CPBDTOPOGXj4mudSstOkliurhrNkVrknOyMlhyVVw+R1M2OwrhnCOhLxHxHY6PJL5UM0m64l\/6cCgtI\/2RWP2r704du7Lg3gPTbvVdP+Da72yQWEahZAz4Koe3yJtUnmRtArX4Zbte8ufsAvNf4k8duOGWVO2sTFWo7BG4jMjl58sHeFN07gTw68LdMlj8NuEolvFjIW9uP2txLL0C7m7bscunsKz0N\/daPZNpPDkZ1LVZXLXl653RrKevzH8RHTA5DFI0fj\/UtdvntGgitra5Rwsajcxxgksx79uQHepmsa1FoWnNOWwfwwxLyDt6YHb1rc1MiWYAXh7aF4yqWXs1KjyCS5xcXd2o8wDOAYWeuLSLha5t9W1+8mvNZaVbxIAx5lW+TJPPGQ3+gqr8Ube8tfD\/AFHULq7hgvI4hIbaM7cT3AdUz3+WMTtnqWz6VouCOFL\/AF+4i4o1yCX4aGViryIQs79VC+oB3H05AViPFziYxa2WhiZraGOXX5N3NHWANbWYcY5q0okcD0l7g869Y6KZJG\/5K6fg9M3nFGUWOl1OHOIiMEQwDlInrtzXzxx0wbiW5so5llisAtohTO3KD58ZAP4y56d6oljp5gzu0kjFncliT3J70pU5elYpkmV77SAoUm0xyEJsIB1pwR+lOKmegpxY\/XnRCQvTGz3oqT5a+lFKm9oszRRRWYtlAGafjhLdqTEmTVlbQA4q1Sp4kqCrU0BTtGsWj03U79QdyxpbLjqDITn\/AAow+9aG9MujcKSQ2YEbXDLpocD5hGEWWfB7F2eNSf4Vx0NL4RjiMV1ZSkKJmjYk9hhoyft5uftVnrWmT3PDcoWIk2d2LuQAcwksaRsx9hJEFPuw9a0GNhkt7lyl1dh10GVP26h8hHr8yubW+kXt\/N8PYWc9zKekcMZdj9AOda7VuE7a60+Dhax1NG1zQoPOuIZ2jgil84ozxRu7jMkTOAVIy2HI\/DzvLyThZNMt9Js+Lb2xsRDG1xFYaZvlnnKDzGlZ5I9wDZCruKqOnMklrUfD\/gjS7KTV5NR1jUdO+GWaC7U29os8rKD5KjdK28EkMMfLtJPKm9gII378\/nxTqnF+1ewuLmEH3RoOTtkkNGxI0gzmQcY5lqWjato8oh1bTLqzduaieJk3D1GRzHuK3Md3Jq0drPeMZJNSskkkcnmZsyW5fP8AEWihcnuUzVW3EGlppF5w3pXD13JFqARYlu73zzDMHBEkarGuH5FcjqGIOavhp381iCxYq9xZWy2YVSD+3BdmGf6s0yrn\/wBN\/So6FMMJ0nH1Vu9uH1GN7Zul8mNsiBJwTGYxPKZXOb+ZLq9nuYk2JLIzhT2yc4qPg1NvorcXs62gxCJGEfPPy55c\/pTHl1UdSzK36bhpEJnBopwpSSntUZpkKQOlJqXfgpHZxnqtuCf7zMw\/RhUTFTdZYG8VdpUpb26EHqCIkB\/UGkAhplMcZqNHifp9VCqRp8PxF0kQGcgn9DUetdwXoPngalcuI43JVMjmQCASB3649PenUGa3gKO7ri3pF5Whu9KcWrokbMyaNOFAGTnEY\/1qng4Xjh4gZLnLsYpXEEfX8OPmbov4unM\/Sux2OhWtwHDFQTDDFkcjh3UHn9BWg4U8PdKfUzqck8TsyQfJ3HmTxqf0X9a1SGOz3QuK\/XV7UFh5h350+a5rqfD91PxbNpm1\/IgsUl8oA7QzyyDdj1wOtcdis3k1wWMaksLnZy9mr7x4N4B0rX+MtXkuJYYmSxs0VpG2qP8Al5XyT2G6uceD38nPQ9S8RZbm+4ksJ4\/i4wIVlBf9ruc8vbGKK9AVoI2ByqfDePCwD2VhksbpHeefhkjdfK\/EdtPaa7f2ly7tJDO8ZLkluRwOZ9sV2jwS4GnvdHh1t4W2SSeZuI67Yrof6Cuoce\/yXtA1HjjRJf8Ai\/RY\/wCfLiaaf9vyjX5FEb+jgtu+lfSOjeD3DnBXhbp1hZSwTBdMvJd6cwWW0Ruvf5pGP3p9taijckvPPHzVDj3tY294KwWYOogF08hJb\/6C+NPDTw4uLjhC0uPh2xdyWkoOOuRuz+tbrgbgVptV4x2Q5ZNUMA5fwxQNj\/HX15wD4McL2XBWnxRtEVtEQKBjBCNEgHvyz+ZrNeAHCOm6jxN4j2VwUxFxBqCKxA5bbC0INWg+jT0RyOfgVzFe94jxA3ZMDU2W57qlLfyXwx4wcAy6LwTp9wYSPJS4uQcdpJkb\/wA64PX6p+KHghoPGHhro8T6tYae99Y2duZbqTZGnmouWY9h8o\/I18qyfyR+HTJrV1\/x1o\/l20yxxQC6+dd0ijp6AEj68qpXNmblwfS7hPwXX+z\/ALYW3D6D6PESQdby2BMtLsbeK474GcLS8S8V\/JEXFspYnHIZjf8A2FfRx8MZ5eANDC25HxWo2sg+Xri5Yn\/2mut\/ydv5N\/DHCPD13fprNjf3M9ikrS2zh13FF7+vzEfeu8ScA6JacMcI2aLEyx8TLbA9fkD3R\/8AEVZoCnaW8HJz8pXO8b4rc8b4wP0\/u0xoLSefvaTjzlfml4rcFyReKdnaeSx80OjYHYI7f7VS+EfAlzqHFklv8O2yJ7cE7eXz2srn\/IV9x8ceFugXvjI6tLbr5OmancJk8lMc8EYB\/usfzq74a8CeGOEJriW0vLSd5buYq0bAlFiit4lU++Hb86k7Cm64n\/l9B91D\/my5ocCLQ2T2IzPMVHt\/\/PqvnrXvDa4n4hu41tzkQWtuFx3y+RXFfGXg6c69xRLHEf2V6ZEOOgCRL\/4mv061fw50KDXrK6Xyy17qkZcE9NvnkD81Br544o8LdG4nXji4lure3e0u5ipkOFI82Yf5IKKzqVcaRz\/qouB3t7wur29fOkaYHQ08\/DPovzcowcBscicV3jUP5N+mx61e2EXHWirHaQq4PxQxIT3TlzHp65FVsPgbZzx6JYni\/Rw17DPcSSm4ATO\/YAD6DZk+hZfWsQ2NRu69ep+0vD6oBY456HuJ+i4\/Zwm5u4YACfMkVfzNPalaNZX0lsRgrg\/mAf8AWu+8L+B+jWusz3J1mzlW1lASMPubIcjOPTAH3rO+JvhtaWdlNq1rfW8k4l2JFG2XbkgC49am\/SFrIO6r0vaW2r3LWMnScT1MH6rT\/wAkjhLTZ9UueIta0mO+jvDJpsCykhY4lQSXE3LrjMEfofNIPXB7NxZqEXFvHUmlXDeS1q0cOmnOQgAB8s+uTk\/U++KlcGcFT8FeHKS2EttZwcMLFYXM7orm4m3F73AHzH9u4jGSP\/l17AE0Oly\/zzxVc6taWjqNwnjTOXaRh8i57AYJOMfh55Fatqzs6DR\/uz5Lx32m4iOK8buLljpbRaaYP+1wgnpJmD0EGFM4E4J1zUuNRo8KwW\/wdrNKXuZliRkRCSVLEbix6KOZyBWz0zg+xGrrq\/Etvb6n5RxFavKBDGv0H4j3OeXtTugaP\/NO+8lk82+uCHnmI79lX+qP16mrgxZkKpgD8X0HWr9KkAMrgeJcVqXFQ9mY92CRgnvg7iZ8fktHxFqVhxHw3Ppdhd2ml3wVYrH4hwsRmb5I0UjuSQAO9fFHjZr1lJZ6hJZyPLJrd5BZ2rdFi0yxhVET+sXJgJPL5oX65r6Y8VFXhfTG1uSWOZdLs5bqzjRxvN3MnkW7leoZfNmlX3t\/Y18eeMVxaDitOGtPctb8N2kWls2c7rlQWuTnuPPeUKe6qtZ3E6rnVNB5fn2Xo\/8ACjhNG3tDdUzOsk+AEACd8mSsEqZ6DNOLGMc6cVPSnUQY51mQvZXPTaxn0p1YwDg04qEj0FOqgzkDnToUDnpjYv8ADRUna3pRRCZrWGo74oorLG66ZSrcDIq6skHI1SW5wRmrmzkGBWgzZZ11K0mkSC1uFlKB0wVdD+8p5EflWtFxPb7LzT1S4OPnjc5E0bDDqVHUHluXqCNw9RiLWYZAzVvbanLbAqjAq2NyNzU46ff361apugLlb22NV2r8KeutC0bVPMm0XUorSXOfgb6TYw9klOEYD+sVP1qpl4M1Ld\/zFzpttH+9LJqEO1R64Vix+wJqfeaqt1LvntIHBwCWBLf9wIJ+9MyS8PqdzRbu+FhY5\/OTFBDHZj6J1Gpc0hAJ+GojzkeoPiUxp0OkaTdMukNJqV6PlOoCMpDaju0QbB3dg7gYySFJwQzrmoR6dB8JaEJO3JQgIMSjo2TzBxnaDz+ZmPMjC9S1thYxPpdt8OqSsnPaSpwCGUAAAkE88Z5dazYjZiWJLEnJJ7mmOdA0hX7e3NV3a1vUyTHfyjoBHrKor7K7L6ygu1xjLJtce4ZcHP1yPagWmkXDBUnntCf+qu9B9WXn\/hNAgNBgNRT3rSwDLTHh9tvRMXGj3MW9o1SeONdxkgYOu31OOY++DVnYcHmdojdySL5uAIlX584z2yfoAGbuVA51eaFpq2Vktw8f7SfDE7dzEZBVVHr0PuWTsDVkuna1rt\/ecNcM3FtbPZ2rNql\/PcCJFQOA8YkP4YwzAHu5DM3LkJW0gckLMr8Ue2WtcABu44EbT8do3JCrbbT10cNHZ2lnaFsBvidRjhlfHqrXCn\/CKTfWC3IFxf6apDsE5\/tY5Sf4JFdst7LKD6K3Smbjw30uyO3VfErhaBvSCeS7\/WFGFe6hoI4M0a14n4f4hg1\/StQmexvYjavFCxA3BGDHLZ2sQcKQUyOxpxBAyMeI+ShFWlUeDTqkucYB0vAJ3jWZbMDGegWV1G1i0W6cQ2jygr8jzruRQTyZccm6EZYeuVBFe6FqtzFqXmSzMxkUhiT6Dl\/lVhrtku\/ULUzSyRrHHqli8h3M8UgUlSe52sCfeM1mYpDFIHHUVQeTSqCNl0NCLqgdWSRv4ifzqu5T8Tz2kM00bdNMacD3jMRH+ZqLo3iLd6bxTIokO0wsSM\/wGNx+qmsle6j\/AMtEhbJm0aZT94kP\/jWTj1Jzqb3ZY81kH5qRVx9YUzA5wsC34WLlhNTJAMeZ\/ovqCPxJutL451COCYrHNp1qeR6lTLGf0rhPB\/iFrXCvHzara3svz3bA\/Of4ztP2p3V+Imi1\/wCN8zO+xbn9JZCKwXnMLj4jPzb9\/wB85pLm4LS3SdiU3g\/A6bWVO2Eh7Gtz0kLc8feIWuajxndXkF84SyvZZLcbjyYgKT+Qr6g8H\/HHUdb8NrHRtQuS1xFDNbkluoaCVP8AKAV8TTytPNJO5y0jFj9Sa6D4UcQS2F0tp5hCidNoz28q4z\/76LO7d+oJccFQe0vs5Qr8HFGk0A0wII7h\/XK+vPDHx71KXgjRvOvm8xFtVm+bkWZEJz7ZQVb+FPiVJomsceSxy\/Nc63clju54e1tUz+lfGXA3F01lw9JbPKR5V1bIOfbdgfpXQODuMXi1ri2JpeTTJcZ+qqP\/AArRp3DaopyPyCuI4j7L1LM3hpOI1CB0mpSOPJdM8fPGC8k8OrS1tLtsDT1hUBuW5DEg\/LLfma+Qn4x4le4ubk6tOJLti0vz9SSD\/mBWm484kn1HhnR7VpS2+S8Lf2fPyv8AlWArKvrlxeGtMAAfJeg+y\/A6Nha1C9gLnvecif5j9l9N\/wAlrxn1zTLq94bv79zbyQ7I8uegRjj\/AACvqmHxtkPA\/ClxJNueDVobqQluZdpph\/5\/rX5u8A6vJpHEtrMrlVcsrfdGA\/zrtC8ZS3XAlkiTHMOs20X\/AG3WT+lX7O4FWhoqZift9Vx3tR7NupcWF5ae6HmmDHQk\/MArpvif4zX9p4v27pLuF1FcwOQ3ZwJCf+6IVG8IvH7VNR1+80q\/umKyXEUu4tzLS2eX\/wAUK188eJ3E0knHa3yyZEMZwR6neP8AWqXgLiGXTdejuGkILunPPdY3Uf8AuoN9puIH+76BT0\/YujW4HocPe7EN89TnH5n4r9F9V8abiPiaVpLotFb3dvdqpPRT5g5fZjXz14s+Kl1Y33FtnFclQ13IXAbkWJ3f\/wAn61kuIeM5JNcuCs3N9OtX69w0n+1cy8XNakueJNbVW5Xd9vP08mH\/AGqe5rtY3UwZH9VkezXs3Ufctp3JJa5uog980yfksPNrWrTzG4kv5i7LtzvP4fSl\/wA73wsra2W5kHwzSBPm\/CrBeX6VXgZNLA51z7Hu717QaNPA0jH9lp+G+MdZsNahunu3fzZVEmT1G7P+ZJrrngmn\/FHi4utazay32j8KxjWJrVBn4m4GxLeHnyO6doxg9ga4DESjq46qQRX2b\/Jo4bfR+CdOkNpsvOJrl9ev7l1zssoS9vZQgd98huZcf+mlXaOqsRSnc\/3XL+0lW24LaVuKaQHNYQPH+X1wup3PCF5dvfW1hrsyaJNbtE8U0I5luZkJzzkLktn3PavOH+F9L4dsRBaSSXEm79pMyhSx6DA54GB\/n61vRoV5rCR2lrbNZ2UfzNK5+aV+7Ed\/Qdq0Ok8MaVo+JUUSyqOckvb6DoK6tlvJkD86L5AufaJ7KZZUdJOYEZ6uI3J58+9YzT+Gbm7jN1co1pbINzSytjl7DGa5dxpxrLe6nJw7wubiO3hbymuEIMkxzz\/sgE45Gug+L\/HElnprWlhOYkmJSOTHNj3YeuO3uQa5lwVolymmXfFkNkZDbstvpcLHHxF7IwjjJJ6gM49s\/Q1DcOAOhnmVv+z9s99H\/ELtskkNY3\/kTA8TOOmTyVLxdNaQjSv52u\/MOm7uJtUfcdslpp0bW9hbn\/7tyt2Pfz0NfKdzcT393Ne3Ll5riRpZGPVmY5J\/M127xi1nT4dH1oaDqHxenalqUXDun3JxvubLTEUPKfQSSNDIMcizSelcTVcchXOPOp2o819LcEoC1tQwD9oDRiMAAHHLMpKoByHM08qADpmvVTH1p5Ex9abC0nPSVT1HKnFT7UpU7kU6qZp0KBz01sHqaKf8v6UUqZrXOKKKKx12KXG2DVhb3GAMmqzpTiSYI51ZpVORUNSnqC0trc8s5qwS55c6zNvc4wKsIro9jVoOWTWtsq3acHvUeVxjNRhck8s155m88qdKgbR0qbaRrc2V5an8SqtwnuVOGH\/axP2qMkHtUvSMJfRFzhWOxifRgVP6Gl\/DtG7Iy80JU\/WliQmF+h7h5\/T6KKIfY14YfY1axabdyrvjtZSD3CHnUiXh++RAyKrkjOMlSPbDYyfpmjQSojdsaYLle6FNb3Gqw\/CMsvwrqYh\/WVWKD7mKKrHw00LT7jgzWZ76ZlOsS\/ByTGTb5SorOTnHRskEk9SuAc1kNHmuNH1BZX32zK6YkZTiORWDIT915+2a1VtxBxDwpZXx4WgknsruX4nyY55VfT5SjqwKxsCyEOCG5q2xD1BFWqThgnlPque4jQqljqNucu0EZj9pnfbcg9YjmAZ0nhlotoZPgPD271CCNyvxd9f+REwB\/EpjlIwevOnuLbLR7Hw81PR7W50iOwW1jv47SIROyXhCozK\/l722t8gYSZPPlgmuNXUl9qVzunlnup3OMuxd2P3yTWhsrbWrDSli1tHltYPmg0naBJO27cBJgblj3c9pILdFHUhBVaQQ1sfngrNXhNwx1OpcXGotcDGcweWpzhPUBoEkkwmHSJtW06GYBl0nRYIroEcizsW2++BNg\/2T6VgTzJNarVLxbOyuGmnW41HUJHeZ1IwjHkxGPQFlH9psdATlT1rMujMBdfw2mWtLj0HwmT4SSrz4wzTohORFprp\/+hVH051ItJSJnZj1gkX\/AAEVG6ioaj9cFXaVMUyQO4fVTr+7ab4aQnJFuUP3d\/8AeoVBJIAPYYopj3ajKkYwMEBFWGg3rWOqW8wYgBxn8iP9ar6FJVgw6g5oY7Q4ORUYKjCw81LtL17a2miU43vG\/wB1Oa1ug6yyHiO9VuclupH61hqstMuTFZajHn+lhC\/rVihWLSB+c1SvbVlZhxvHzb9k3f3j3FnYQMciGJ\/zaRjUKgkkAH90YFFV3u1GVdYwMEDr6mUuCUwzxzKcFGDVsbbWjDwpaQFiN+qLKR9HLVi6lyXLfzfb24PJHZ\/vUtGoaYPh9lWu7ZtxpB5GfhKc12+bUdUnuWOcsQPpk1DglaCZJVOCjBvypHU5Peioi8l+pWGU2sYKY2GFt+INcddVimVjiXTY1\/Jm\/wB6pOMbz4zW7iXOdzK\/5xJ\/tUDU7k3BtWJyVtlQ\/maavpTPc+YTnKJ+igVbq1S8FvVULSybQcx4GQCPUfZMgUsCkgUtR3qNoV8lXvBHDF1xnxdo\/CtlkS6peRWob+AMwDMfZVyT7Cv0r4d4MstS4ettb0yza0htgj6LbhmULaRRLFbbhnGTGiOf6zE18bfyUeFRe6xq\/E0kBMiQHSbGTH9HJOjefIP6y26ygejSLX2np3EOq6Zaxst1HIgOwxSkttUDl05jPL8q3eE0W6nVX+A+v0XgH8ZeM3DhR4XZugg63ddwB55mfqrKG5mmhSQyOCygnJPXvXLvFPxBkUScOaXdyKvS6ljfDMf+mp7D+I\/b1q+4+49trOy+C0UMuqXuSIUyxjU9XXpnJzgdeprkEmkRWNxFLr\/mGeQhzabgsmwcyXAzsGAeRwfatO4qn9rV5j7N8HYXi8u2xH7W8zHPwHftzSLRLvWdSsdPuL9reElEaRnOyIOc8vfBH1I+9dM8TdWteFNFi0+1k8m24f086mEDDfJcs629oo7k+bK0p\/8Ask9q55b6Xd8WahJLpWky21u0rOgD5hhBOcZIycfUnlVV4p8QX19c2N1fSJNbJffFyesltYQyRgkdQjXHxI9CdvfNU3P00nDvwu0oWX63ilB04pAuLcb4jvycx4Y71ybxps7XSeLYeHNP1a01CDSbKODdaxeXHHKzNJLGE\/dKu7Lj+qB2rCouB70ue5uL66mv7uVpZ7iRpZZGOSzsSST9STSkGBnvWQTqMr262pG2oMouMkCJ716iY+tPKuOleKuKeRKISPcvFTlTyJXqpntTyp2pwCruem9hop\/YKKWFHrXKaKKKxV3iKKKKUITkbsO9Sopm6VDSpER54q3TMqGoAp8Ts3U1MgFQof8AWp0B6VOFnVcK60fTWv5eZ2xIRvbvz7D3P+56CtT8JPI001usFvbgiaa4n5xozdAq45sQMjlk8yABTOhWjrbw2sMaq7sqksc7nfb+nzoD7K\/rVpq+mWdxJCt3xZYWVkkYe1ikWeSaZD\/9YrHGVDORnmwxyHarbGQ2VyF3d9pW08ugJ9BMk\/D4Qa95+Hoz+1Gqam\/eV51gX7LhyR7kj6V7ENHuTt0y+u9LuGwBHdSCWCT2LgDH3Uj1Iqw0zhi11EA6VYcSark4zb6aEU\/Rgz\/5Cr6Pwo4peIXMXhprckeQqtdXIjViegwFBPTsakax7th+eIWfWv7O3MPqQergP\/lxA9B0WN1CymaAwalZBLi3kKOhbaFwRnn2XBzjpggjlmqiO+a2ZfgNRVRGcok7FHhPoki9vuPpW\/4w0w6Pqj2E1qYDaXL2Etuzl9ioImVdxJJwszpnJ5AVye6URySRg\/hYr+VR1h2boWnwl7b+jq5HI7s\/H0PmtDPxXq0cTHUNamKEYxb6g0jv7HEgOPc5+lZjUOJriRtlnbpBF0wTliO+SMDn3IGT3JqFP6VCm61XfUcea6G04fQpmdI+ihSDnTJ60\/J1phqpVVvM2XisVJOexFeDpXtFV09FFFFIlRRRRQhFKRyiuB+8MGk0UoMGQkIlFFFFIlRQTkAelFFLKRFFFFIlXrMW2+wxXpOTn2A\/Sk0odKlblNIhKApxR60gela7wv0Ow17jbTbfVwTptu5u77GP6CIbmHP1wF+9WabS4wFVu7hlrRdXqbNBJ8l9deAWhQcM6BpNnpizI1rYb7\/zYxiTUbkiSQdTuVIktkwR13V1jV+NvDLQLdJOL9StdFnA5hbhRvPosZOT9AK+H+JfFbiLU9Vu9N07WbwaQJXmiSFvhkCuxYyO8ZDMSWJy3sAByFUenaToOqcR6ZJqM97YWNwyTXFxcv5rOgYlmCnDYKjlzPXma2KN6KDBTptnxXh\/GPYJ\/Hb5\/E+JV3MDsgMEugDAOd45aXZ2ndfUnGnj94K8J3d1Nw1ZazqepXGVe9FsyNGcY8tDLt2Y6chkY71xq+8aLzUL1Xs+HbayWXnuu53u7ll6lm\/CMYGcsOnqOVda8e9S4F0jgXQOFODlsLnVZZ4TELdkaQxgfMTnnuJ+\/pXzfDZaxpOuXvD+t2irem4XT5Xa3VpY3Z+bqcZJwvvkE+oNJcV6hdE46BWPZXgfCzZmv2bi7kajyXFogTphogTtBHILap4gcc8V8RWemz6hqR0y5u4kt7KwkaEyQuy7VIiC8trDJPvj2leMHE6XF5qx0xf2N8y6ZGxJIW0j8uQKnYZZFcnnkyNnrV9DwfrfhxdalLxVGLjXItNS30MxMZmXIjj87yx+BRk4ZsEFsAHnt5FxVcebfrawuxt7ZFUbjjMm0buWeowF99gNR1C9jS1+61eF0LO+vGVrRoFNgxp\/a7Z0jvyGid5DhyVKozin0GTTaDH3p9R2qoF2bylqtPIo6UhB3p+NTjpTgFVeUuNTnlTyL+VJUdKeReWKeqrivcD0opzYKKFHK49RRRWIvREUUUUISlPOn4zg5qMDinkarNIqN4U+E+9ToHqsibpUyJ8HIqyCqFVsrfcG6gksttbSERi2mikZieqmTBP23D7CtroXjRqfAthb6DZcDcPfzpppa3l1C+tjLcZDHkCCu0D6n9a5Ro0khkWSzjDzxBi8Zf8ApUIwVC9zjOfb6Vp86XxTGhaeWO+SNUWYKZGcKMBZkHzEgcvMUEkDmuedXKVV7R7hgrjeKcMtbioRds1UzkjODncA5Bk4z4YXa7nxo8QZb\/yJta+Ggj1S0tJniiihVEMW4ktt+VZX\/A5\/Cq8yc5rn3HPiB4iXFjYG84o1dFuFnt7uNbyRM3SSHzInQEfhVowBz5EHOScVrXutvcjyLrSQFks2EZWWTKWqbIo2XZll7kY5nGegph7pYvInurxr66sldRPMgVIZHdnJCnmzlmJ3SYPTCnAqxUrVKgguPx6rnbHgtlZVG1KdFkiMBon9pG8QPe+IE5KSI57KztLK4y08bNcyITljNIUO0+4CRg+hc+hrDapNG93K0QXZuwNvQ45Z++M\/errWNeiWAw2Uu95R8zg9AevPqSct37knmeWUllqlVcDgLtOGWz2zUfz+8n12TUzA86gzN1qRLIADUOVuxquV0VFqYkPemT1pxzTdVapV5ohFFFFQJ6KKKKEIooooQiiiihCKKKKEIooooQiiiihCKUB0FJHWlipmJpSx1ru38mvhLSeJbfifT9S1eKyk1DTjCE3R+dNCrh2WMPnqyLl9rBQvMZIrhSAswA6nlVqusXtrcRvpty9qbZBFHJCdjgdyGHPmST171coPFNwcRKxuOWVXiVm+1oP0Ods6JgggjHku18Q+C\/iEmlrepwvp+iaemEsGju4ZpLnDMcs27oN34ztx2HPA0el8KeC3D\/DdzZeMXFa3mu3CpFv0aZr6S2RAFCLNEHhJLAtzY9cVw+HxH4jKxLcNb3AhVlUSIcHIwCVBCnB+YcsbgCc1CHFGvmF4U1KWJJDlxCBHu+pUAmrQrU2mWt+OfsuTdwHil1SFG6r6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Visive&#8217;s Image Recognition is driven by AI and can automatically recognize the position, people, objects and actions in the image. Image recognition can identify [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[32],"tags":[],"class_list":{"0":"post-55262","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-32"},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.4 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>AI Finder Find Objects in Images and Videos of Influencers - Presse Express<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/presse-express.dz\/?p=55262\" \/>\n<meta property=\"og:locale\" content=\"ar_AR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI Finder Find Objects in Images and Videos of Influencers - Presse Express\" \/>\n<meta property=\"og:description\" content=\"What is Image Recognition their functions, algorithm In this article, we are going to look at two simple use cases of image recognition with one of the frameworks of deep learning. 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