{"id":1027404,"date":"2023-08-06T16:56:49","date_gmt":"2023-08-06T20:56:49","guid":{"rendered":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/uncategorized\/the-hidden-impact-of-ai-in-photography-and-how-machine-learning-cryptopolitan.php"},"modified":"2023-08-06T16:56:49","modified_gmt":"2023-08-06T20:56:49","slug":"the-hidden-impact-of-ai-in-photography-and-how-machine-learning-cryptopolitan","status":"publish","type":"post","link":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/machine-learning\/the-hidden-impact-of-ai-in-photography-and-how-machine-learning-cryptopolitan.php","title":{"rendered":"The Hidden Impact of AI in Photography and How Machine Learning &#8230; &#8211; Cryptopolitan"},"content":{"rendered":"<p><p>Description        <\/p>\n<p>      Artificial Intelligence (AI) and machine learning have been      quietly transforming photography, altering how we shoot and      edit images. While more attention-grabbing technologies like      Adobes Generative Fill feature in Photoshop have caught the      eye, AIs subtler integrations in the photography field are      playing a significant role. Here are five ways AI is      invisibly enhancing your photography        Read more    <\/p>\n<p>    Artificial Intelligence (AI) and machine learning have been    quietly transforming photography, altering how we shoot and    edit images. While more attention-grabbing technologies like    Adobes Generative Fill feature in Photoshop have caught the    eye, AIs subtler integrations in the photography field are    playing a significant role. Here are five ways AI is invisibly    enhancing your photography experience.  <\/p>\n<p>    Modern mirrorless cameras utilize machine learning algorithms    to improve autofocus capabilities. While traditional autofocus    systems rely on contrast detection and perspective analysis, a    parallel process fueled by machine learning models is now at    play. This AI-driven processor interprets the scene in real    time, identifying subjects such as faces, objects, animals, and    more. Cameras equipped with face and eye detection can lock    focus on recognized subjects, providing improved precision and    ease of use.  <\/p>\n<p>    Smartphone cameras produce surprisingly high-quality images    despite their small sensors and lenses. This is made possible    by dedicated image processors enhanced with machine learning.    Before the shutter button is even tapped, the camera system    evaluates the scene and makes decisions based on detected    elements, such as portraits or landscapes. After capturing    multiple images with varying exposures and ISO settings, the    processor blends them together, making adjustments based on    scene recognition. The result is photos that rival those from    larger-sensor cameras, achieved through the seamless    integration of AI-driven image processing.  <\/p>\n<p>    Image editing software has been utilizing machine    learning-based people recognition for some time. Applications    like Google Photos, Lightroom, and Apple Photos can easily    identify specific individuals in photos, enabling users to    locate images containing certain people quickly. This    technology extends beyond photography to video editing, where    programs like DaVinci Resolve can also recognize people in    video footage. Additionally, facial feature recognition allows    for more accurate selections and targeted adjustments in    editing processes.  <\/p>\n<p>    Auto-editing controls in photo software have evolved with the    help of machine-learning models. For example, in Lightroom,    clicking the Auto button in the Edit or Basic panels triggers    Adobe Senseis cloud-based processing technology. The AI    analyzes similar images in its database and applies relevant    edit settings to improve the image. Other applications, such as    Pixelmator Pro and Luminar Neo, offer similar AI-driven    automatic editing features, giving users a starting point that    can be further customized.  <\/p>\n<p>    Machine learning technologies also assist photographers in    quickly finding images without the need for extensive    keywording. Many photo apps now employ object and scene    recognition to scan images in the background or in the cloud.    This allows users to perform searches based on recognized    elements, such as landscapes, buildings, or animals. While not    as precise as manually applied keywords, this AI-powered search    feature saves time and streamlines the image retrieval process.  <\/p>\n<p>    As AI-driven features become more integrated into photography    tools, photographers are benefiting from improved precision,    automatic adjustments, and simplified image searches. From    camera autofocus to smartphone image processing, machine    learning plays a crucial role in enhancing the visual    experience for both professional and amateur photographers.    Embracing these AI-powered capabilities allows photographers to    focus on their craft, knowing that the technology is working    seamlessly to enhance their creative vision.  <\/p>\n<p><!-- Auto Generated --><\/p>\n<p>View post: <\/p>\n<p><a target=\"_blank\" rel=\"nofollow noopener\" href=\"https:\/\/www.cryptopolitan.com\/impact-of-ai-in-photography\" title=\"The Hidden Impact of AI in Photography and How Machine Learning ... - Cryptopolitan\">The Hidden Impact of AI in Photography and How Machine Learning ... - Cryptopolitan<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p> Description Artificial Intelligence (AI) and machine learning have been quietly transforming photography, altering how we shoot and edit images.  <a href=\"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/machine-learning\/the-hidden-impact-of-ai-in-photography-and-how-machine-learning-cryptopolitan.php\">Continue reading <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"limit_modified_date":"","last_modified_date":"","_lmt_disableupdate":"","_lmt_disable":"","footnotes":""},"categories":[1231415],"tags":[],"class_list":["post-1027404","post","type-post","status-publish","format-standard","hentry","category-machine-learning"],"modified_by":null,"_links":{"self":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/posts\/1027404"}],"collection":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/comments?post=1027404"}],"version-history":[{"count":0,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/posts\/1027404\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/media?parent=1027404"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/categories?post=1027404"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/tags?post=1027404"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}