{"id":10361,"date":"2024-07-01T14:44:52","date_gmt":"2024-07-01T12:44:52","guid":{"rendered":"https:\/\/www.idiv.de\/?page_id=10361"},"modified":"2026-05-06T11:08:07","modified_gmt":"2026-05-06T09:08:07","slug":"ki-tools","status":"publish","type":"page","link":"https:\/\/www.idiv.de\/de\/forschung\/kernforschungsgruppen\/arten-interaktionsoekologie\/ki-tools\/","title":{"rendered":"KI-Tools"},"content":{"rendered":"<div class=\"textbildrepeater pb-24 pt-0 no-bg modulclass \" id=\"\">\n    <div class=\"container\">\n        <div class=\"row\">\n                                                                <div class=\"pb-48   mod_text  col-md-8 offset-md-2 pos_top\">\n                            <div class=\"textrepeater \" id=\"\">\n    <h1>KI-Tools f\u00fcr die schnelle Messung von Besuchsnetzen<\/h1>\n<p>Pollination is critical to many ecosystem services, such as the maintenance of biodiversity and human nutrition. Addressing how plant-pollinator interactions change across environmental gradients requires quantifying pollinator visitation. We need new tools that allow for rapid data collection to increase the spatial and temporal sampling that is possible.<\/p>\n<p class=\"text-justify\">Ecologists typically observe pollinators in the field, record the species identity of the easily distinguished individuals, and collect with a net the remaining individuals so that they can be later identified to species in the lab. This is labor and time intensive, and thus prevents the massive data collection that is necessary to achieve a general, predictive understanding of how pollination responds to global change.<\/p>\n<p>We use machine learning methods and technology to automatize ecological data collection on plant-pollinator interactions.<\/p>\n<\/div>\n                            <\/div>\n                                                                    <div class=\"pb-48   mod_text  col-md-4 offset-md-2 pos_top\">\n                            <div class=\"textrepeater \" id=\"\">\n    <p>A first step is to develop and test a camera system capable of capturing clear images of visiting insects on flowers. Our first results use mobile phones for time-lapse photography, capturing images of flowers every 1\u20132 seconds with the goal of capturing images of insects visiting flowers (Fig .1). The pollinators in the collected images are identified by entomologists in our group down to the lowest possible taxonomic level (order &gt; family &gt; genus &gt; species).<\/p>\n<\/div>\n                            <\/div>\n                                                                    <div class=\"pb-48   mod_bild  col-md-4 offset-md-0 pos_top\">\n                            <div class=\"bildrepeater \" id=\"\">\n    <div class=\"relativ\"><img decoding=\"async\" class=\"responsiv desktop\" src=\"https:\/\/www.idiv.de\/wp-content\/uploads\/2024\/08\/iDiv-SIE-Steen-2017-2.jpg\" height=\"\" width=\"\" alt=\"idiv-Fig. 1 - Camera system for image collection. Adapted from Steen, R. (2017).\"\/><img decoding=\"async\" class=\"responsiv mobile\" src=\"https:\/\/www.idiv.de\/wp-content\/uploads\/2024\/08\/iDiv-SIE-Steen-2017-2.jpg\" height=\"\" width=\"\" alt=\"idiv-Fig. 1 - Camera system for image collection. Adapted from Steen, R. (2017).\"\/><\/div><p class=\"bu\">Fig. 1: Camera system for image collection. Adapted from Steen, R. (2017).<\/p><\/div>\n                            <\/div>\n                                                                    <div class=\"pb-24   mod_text  col-md-4 offset-md-2 pos_top\">\n                            <div class=\"textrepeater \" id=\"\">\n    <p>The second part of the project involves training state of the art Convolutional Neural Networks (CNN) with the goal of insect identification down to the lowest possible taxonomic level (Fig. 2). For this, we make use of our field images as well as images from online databases (e.g.,\u00a0<a href=\"https:\/\/www.inaturalist.org\/\" target=\"_blank\" aria-label=\"open in new tab\" rel=\"noopener\">iNaturalist<\/a>\u00a0and\u00a0<a href=\"https:\/\/observation.org\/\" target=\"_blank\" aria-label=\"open in new tab\" rel=\"noopener\">Observation.org<\/a>).\u00a0We focus\u00a0on four orders of insect pollinators: Coleoptera, Diptera, Hymenoptera and Lepidoptera.<\/p>\n<p >Our main goal is to develop an automated pipeline that can quantify the abundance and diversity of insects that visit flowers and the structure of plant-pollinator interactions across various environmental gradients in Europe<\/p>\n<\/div>\n                            <\/div>\n                                                                    <div class=\"pb-24   mod_bild  col-md-4 offset-md-0 pos_top\">\n                            <div class=\"bildrepeater \" id=\"\">\n    <div class=\"relativ\"><img decoding=\"async\" class=\"responsiv desktop\" src=\"https:\/\/www.idiv.de\/wp-content\/uploads\/2024\/08\/iDiv-SIE-Boussioux-order-sp-difficulty.png\" height=\"\" width=\"\" alt=\"idiv-Difficulty in classifying insects. Adapted from Boussioux et. al. (2019)\"\/><img decoding=\"async\" class=\"responsiv mobile\" src=\"https:\/\/www.idiv.de\/wp-content\/uploads\/2024\/08\/iDiv-SIE-Boussioux-order-sp-difficulty.png\" height=\"\" width=\"\" alt=\"idiv-Difficulty in classifying insects. Adapted from Boussioux et. al. (2019)\"\/><\/div><p class=\"bu\">Fig. 2: Difficulty in classifying insects. Adapted from Boussioux et. al. (2019)<\/p><\/div>\n                            <\/div>\n                                                                    <div class=\"pb-24   mod_text  col-md-4 offset-md-2 pos_top\">\n                            <div class=\"textrepeater \" id=\"\">\n    <h2><strong>How can you contribute?<\/strong><\/h2>\n<p>If you have\u00a0images of pollinators and you are willing to share them with us, feel free to contact\u00a0<a href=\"https:\/\/www.idiv.de\/de\/staff\/valentin-stefan\/\" target=\"_blank\" aria-label=\"open in new tab\" rel=\"noopener\">Valentin \u0218tefan\u00a0<\/a>or\u00a0<a href=\"https:\/\/www.idiv.de\/de\/staff\/tiffany-marie-knight\/\" target=\"_blank\" aria-label=\"open in new tab\" rel=\"noopener\">Prof. Tiffany Knight<\/a><\/p>\n<p>We also welcome your thoughts,\u00a0ideas and collaboration.<\/p>\n<\/div>\n                            <\/div>\n                                                                    <div class=\"pb-24   mod_text  col-md-4 offset-md-0 pos_top\">\n                            <div class=\"textrepeater \" id=\"\">\n    <h3><strong>Scientific investigators<\/strong><\/h3>\n<p><strong>UFZ\/iDiv<\/strong>:\u00a0Prof. Tiffany Knight\u00a0,\u00a0Valentin \u0218tefan\u00a0&amp;\u00a0Maximilian Sittinger<\/p>\n<p><strong>DLR<\/strong>:\u00a0\u00a0Prof. Hannes Taubenb\u00f6ck, Thomas Stark,\u00a0Dorothee Stiller,\u00a0Dr. Michael Wurm &amp;\u00a0Robin Spanier<\/p>\n<\/div>\n                            <\/div>\n                                                                    <div class=\"pb-24   mod_text  col-md-8 offset-md-2 pos_top\">\n                            <div class=\"textrepeater \" id=\"\">\n    <h3 ><strong>References<\/strong><\/h3>\n<p>Boussioux, L., Giro-Larraz, T., Guille-Escuret, C., Cherti, M., &amp; K\u00e9gl, B. (2019). InsectUp: Crowdsourcing Insect Observations to Assess Demographic Shifts and Improve Classification. arXiv preprint arXiv:1906.11898.<\/p>\n<p class=\"text-justify\">Steen, R. (2017). Diel activity, frequency and visit duration of pollinators in focal plants: in situ automatic camera monitoring and data processing. Methods in Ecology and Evolution, 8(2), 203-213.<\/p>\n<\/div>\n                            <\/div>\n                        <\/div>\n    <\/div>\n<\/div>\n\n<hr class=\"modulborder nm np\"><div class=\"textbildrepeater pb-24 pt-48 no-bg modulclass \" id=\"\">\n    <div class=\"container\">\n        <div class=\"row\">\n                                                                <div class=\"pb-24   mod_text  col-md-8 offset-md-2 pos_top\">\n                            <div class=\"textrepeater \" id=\"\">\n    <h2>News<\/h2>\n<h3>2024, January<\/h3>\n<p>Maximilian Sittinger joined our team. We will work on adapting his\u00a0<a href=\"https:\/\/maxsitt.github.io\/insect-detect-docs\/\" target=\"_blank\" aria-label=\"open in new tab\" rel=\"noopener\">AI capable camera<\/a>\u00a0for monitoring plant-pollinator interactions.<\/p>\n<h3>2023,\u00a0September<\/h3>\n<p>Our paper &#8222;<a href=\"mailto:https:\/\/www.nature.com\/articles\/s41598-023-43482-3\" target=\"_blank\" aria-label=\"open in new tab\" rel=\"noopener\">YOLO object detection models can locate and classify broad groups of flower-visiting arthropods in images<\/a>&#8220; got published in Scientific Reports.<\/p>\n<h3>2022, September<\/h3>\n<p><a href=\"https:\/\/malikanr.com\/\" target=\"_blank\" aria-label=\"open in new tab\" rel=\"noopener noreferrer\">Malika\u00a0Nisal Ratnayake<\/a>\u00a0joined the team of Prof. Tiffany Knight, Species Interaction Ecology at iDiv, for a three-month research stay. His research stay is funded by the\u00a0<a href=\"https:\/\/www.greentalents.de\/index.php\" target=\"_blank\" aria-label=\"open in new tab\" rel=\"noopener noreferrer\">Green Talents scholarship<\/a>\u00a0awarded by the German Federal Ministry of Education and Research (BMBF).<br \/>\nMalika\u00a0recently completed his PhD at the Faculty of Information Technology, Monash University, Australia. His research is focused on designing computer vision and artificial intelligence facilitated technologies for the advancement of pollination monitoring in agriculture and ecology.<\/p>\n<h3>2022, June<\/h3>\n<p><a href=\"https:\/\/www.linkedin.com\/in\/robin-spanier\/\" target=\"_blank\" aria-label=\"open in new tab\" rel=\"noopener\">Robin Spanier<\/a>\u00a0presents the results of his master thesis at the\u00a0<a href=\"https:\/\/www.helmholtz.ai\/themenmenue\/news-events\/news\/news\/article\/30010\/index.html\" target=\"_blank\" aria-label=\"open in new tab\" rel=\"noopener\">Helmholtz AI conference<\/a>.<\/p>\n<h3>2022,\u00a0May<\/h3>\n<p><a href=\"https:\/\/www.idiv.de\/en\/profile\/513.html\" target=\"_blank\" aria-label=\"open in new tab\" rel=\"noopener\">Valentin \u0218tefan<\/a>\u00a0started a 3 months research stay at the DLR in the team of\u00a0Prof. Hannes Taubenb\u00f6ck,\u00a0City and Society. The research stay is\u00a0funded by the Helmholtz Information &amp; Data Science Academy &#8211;\u00a0HIDA Trainee Network.<\/p>\n<h3>2022,\u00a0April<\/h3>\n<p>Find out more about our project in the Helmholtz AI News &#8211; &#8222;<a href=\"https:\/\/www.helmholtz.ai\/themenmenue\/news-events\/news\/news\/article\/29783\/index.html\" target=\"_blank\" aria-label=\"open in new tab\" rel=\"noopener\">Helmholtz AI project call showcase: Pollination Artificial Intelligence.<\/a>\u00a0Transferring existing large-scale AI methods to the field of pollination ecology for the automatic classification of insect pollinators.&#8220;<\/p>\n<h3>2021,\u00a0November<\/h3>\n<p>We kicked off our UFZ-DLR collaboration for Pollination Artificial Intelligence (PAI).<\/p>\n<p>Many thanks to the participants: Thomas Stark, Dorothee Stiller, Robin Spanier, Michael Wurm, and Prof. Hannes Taubenb\u00f6ck from DLR, and Valentin \u0218tefan and Tiffany Knight from UFZ\/iDiv.<\/p>\n<p>Robin Spanier started working on his MSc thesis &#8220;\u00a0Pollination AI, Deep Learning approach to identify pollinators and their taxa using the YOLO architecture&#8220;<\/p>\n<h3>2021,\u00a0August<\/h3>\n<p>Our project\u00a0<strong>PAI &#8211; Pollination artificial intelligence<\/strong>\u00a0is one of the 17 funded projects selected\u00a0by the\u00a0<a href=\"https:\/\/www.helmholtz.ai\/themenmenue\/news-events\/news\/news\/article\/28827\/index.html\" target=\"_blank\" aria-label=\"open in new tab\" rel=\"noopener\">Helmholtz AI<\/a>.<\/p>\n<p>This sets our collaboration with the team of\u00a0Prof. Hannes Taubenb\u00f6ck,\u00a0City and Society.<\/p>\n<\/div>\n                            <\/div>\n                        <\/div>\n    <\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"","protected":false},"author":3,"featured_media":0,"parent":10359,"menu_order":1,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"advgb_blocks_editor_width":"","advgb_blocks_columns_visual_guide":"","footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-10361","page","type-page","status-publish","hentry"],"acf":{"search_thumb":"","search_kurzbeschreibung":"","breadcrumb":false},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>KI-Tools | iDiv<\/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:\/\/www.idiv.de\/de\/forschung\/kernforschungsgruppen\/arten-interaktionsoekologie\/ki-tools\/\" \/>\n<meta property=\"og:locale\" content=\"de_DE\" \/>\n<meta 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