[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-119400-en":3,"doc-seo-119400-105":30,"detail-sidebar-cat-0-en-105":95},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},119400,687197207057,"Sage","https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0",8,"Research & Report","Leaf it to the AI: Visualizing Foliage with Machine Learning","This research project aims to develop a tool for aiding in the research and monitoring of the threatened prickly cacti. The project utilizes machine learning to analyze foliage data, visualizing current and predictive locations of foliage within a region. The development provides visual patterns for the foliage's distribution. The machine learning model identifies patterns from the data and provides predictions for researchers. Visualizations are generated by comparing the output of similar algorithms. The poster showcases the implementation of visualization and machine learning for foliage analysis. Key components include Python, HTML, and CSS for web maps and the original dataset used for web heat maps. The visualization implementation section highlights a scatter plot of foliage density by coordinates and a heat map visualizing foliage density. For machine learning implementation, Random Forest Regression was used to analyze datasets and generate predictions. The training process involved running the algorithm for a set duration to model both latitudes. The model's accuracy was evaluated by comparing the predicted coordinates to actual coordinates. The visualization maps the results, adding the machine learning component to develop these maps. Future development can create an interactive map where workers can visualize foliage with environmental data such as weather, soil, and regional location.","Digital Commons at St. Mary's University  \n\n| Research Showcase Posters-2025 | Annual Showcase-2025 |\n| --- | --- |\n| Spring 2025\u003Cbr>Leaf it to the AI: visualizing foliage with machine learning\u003Cbr>Chelsy Tinacba St. Mary 's University\u003Cbr>George Sikazwe\u003Cbr>University of Incarnate Word\u003Cbr>Michael Frye\u003Cbr>University of Incarnate Word\u003Cbr>Follow this and additional works at: [https://commons.stmarytx.edu/rscpos25](https://commons.stmarytx.edu/rscpos25)\u003Cbr> Part of the Environmental Education Commons, Environmental Health and Protection Commons, and the Environmental Monitoring Commons |  |\n\nRecommended Citation  \nTinacba, Chelsy; Sikazwe, George; and Frye, Michael, \"Leaf it to the AI: visualizing foliage with machine learning\" (2025) . Research Showcase Posters-2025. 22.  \n[https://commons.stmarytx.edu/rscpos25/22](https://commons.stmarytx.edu/rscpos25/22)  \nThis Book is brought to you for free and open access by the Annual Showcase-2025 at Digital Commons at St. Mary's University. It has been accepted for inclusion in Research Showcase Posters-2025 by an authorized administrator of Digital Commons at St. Mary's University. For more information, please contact[sfowler@stmarytx.edu](sfowler@stmarytx.edu), [egoode@stmarytx.edu](egoode@stmarytx.edu).","cbCainZqrt6NYxu2","https://ap.wps.com/l/cbCainZqrt6NYxu2","pdf",911535,1,2,"English","en",105,"# Abstract\n# Acercifolius Data\n# Visualization Implementation\n# Machine Learning Implementation\n# Acknowledgements\n# Results","[{\"question\":\"What is the primary goal of this project?\",\"answer\":\"The primary goal is to develop a tool to aid in the research and monitoring of threatened prickly cacti, specifically by visualizing foliage using machine learning.\"},{\"question\":\"What technologies are used in the visualization implementation?\",\"answer\":\"Python, HTML, and CSS are used to embed the web heat maps and original dataset into interactive web pages.\"},{\"question\":\"How is the machine learning model trained and validated?\",\"answer\":\"The machine learning model is trained by running the algorithm to model both latitudes. Validation involves printing the mean absolute error and comparing predicted coordinates to actual ones, as well as visualizing the patterns.\"},{\"question\":\"What are the potential future developments for this project?\",\"answer\":\"Future developments include creating an interactive map that incorporates environmental data (weather, soil, regional location) for more comprehensive analysis and visualization.\"}]","Leaf it to the AI: Visualizing Foliage with Machine Learning | PDF",1785724107,5,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":90,"head_meta":92,"extra_data":94,"updated_unix":28},"leaf-it-to-the-ai-visualizing-foliage-with-machine-learning","",{"@graph":36,"@context":89},[37,53,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,47,50],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":21},"https://docshare.wps.com/document/","Document",{"item":48,"name":12,"@type":43,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":43,"position":52},"https://docshare.wps.com/document/leaf-it-to-the-ai-visualizing-foliage-with-machine-learning/119400/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":23,"description":14,"dateModified":61,"datePublished":62,"encodingFormat":60,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":41,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-08-04","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81,85],{"name":72,"@type":73,"acceptedAnswer":74},"What is the primary goal of this project?","Question",{"text":75,"@type":76},"The primary goal is to develop a tool to aid in the research and monitoring of threatened prickly cacti, specifically by visualizing foliage using machine learning.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What technologies are used in the visualization implementation?",{"text":80,"@type":76},"Python, HTML, and CSS are used to embed the web heat maps and original dataset into interactive web pages.",{"name":82,"@type":73,"acceptedAnswer":83},"How is the machine learning model trained and validated?",{"text":84,"@type":76},"The machine learning model is trained by running the algorithm to model both latitudes. Validation involves printing the mean absolute error and comparing predicted coordinates to actual ones, as well as visualizing the patterns.",{"name":86,"@type":73,"acceptedAnswer":87},"What are the potential future developments for this project?",{"text":88,"@type":76},"Future developments include creating an interactive map that incorporates environmental data (weather, soil, regional location) for more comprehensive analysis and visualization.","https://schema.org",{"og:url":51,"og:type":91,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":93,"canonical":51},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":96},[97,101,105,109,113,118,123,126,131,134,138],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Story & Novel",90,"story-novel",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Literature",80,"literature",{"id":52,"doc_module":4,"doc_module_name":46,"category_name":106,"show_sort_weight":107,"slug":108},"Exam",70,"exam",{"id":29,"doc_module":4,"doc_module_name":46,"category_name":110,"show_sort_weight":111,"slug":112},"Comic",60,"comic",{"id":114,"doc_module":4,"doc_module_name":46,"category_name":115,"show_sort_weight":116,"slug":117},6,"Technology",50,"technology",{"id":119,"doc_module":4,"doc_module_name":46,"category_name":120,"show_sort_weight":121,"slug":122},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":124,"slug":125},30,"research-report",{"id":127,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":129,"slug":130},9,"Religion & Spirituality",20,"religion-spirituality",{"id":129,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":129,"slug":133},"World Cup","world-cup",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":135,"slug":137},10,"Lifestyle","lifestyle",{"id":139,"doc_module":4,"doc_module_name":46,"category_name":140,"show_sort_weight":29,"slug":141},19,"General","general"]