[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-134752-en":3,"doc-seo-134752-105":30,"detail-sidebar-cat-0-en-105":92},{"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},134752,13056703019404,"Miles","https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0",8,"Research & Report","Real-time Italian Sign Language Recognition with Deep Learning","Image recognition systems can support communication for people with hearing impairments who rely on sign languages. This work builds a real-time automatic recognition system for the Italian Sign Language (LIS) alphabet using deep learning and fine-tuning. Two convolutional neural network models, CNN and VGG19, are implemented with OpenCV to identify user-provided alphabet letters in an HCI setting. Experiments compare architectures and leverage a recently released open-source LIS dataset, enabling research on single-handed isolated signs and promoting LIS interpretation, learning, and inclusion.","Real-time Italian Sign Language Recognition with Deep Learning  \nVeronica J. Schmalz 1,2  \n1 ITEC, imec research group at KU Leuven, Etienne Sabbelaan 51, 8500, Kortrijk, Belgium 2 Freie Universität Bozen-Bolzano, Universitätsplatz, 1, 39100, Bozen, Italy  \nAbstract  \nImage recognition systems have evolved so much that they can actually be exploited to solve significant challenges today, such as facilitating communication for people with hearing impairments relying on sign languages. This project aims to apply deep learning and fine-tuning techniques to build an automatic recognition system for the Italian Sign Language (LIS) . More specifically, our goal is a real-time image recognition system capable of accurately identifying the letters ofthe LIS alphabet provided by a user in a Human Computer Interaction (HCI) framework by means of Python’s Open Source Computer Vision (OpenCV) library and two models based on convolutional neural networks, namely CNN and VGG19, applied for large-scale image and video recognition. In addition to testing the performance of different architectures, our work constitutes a novel step towards the application of automatic image recognition techniques with the recently acknowledged LIS and a lately released open-source dataset, also representing the only source available for this type of research on single-handed isolated signs. This project may not only play a role in the interpretation and learning of the Italian Sign Language, encouraging its spread and study, but also in the inclusion of hearing-impaired individuals in the language research domain.  \nKeywords  \nsign languages, image recognition, deep learning, Italian Sign Language  \n1. Introduction  \nSign languages (SLs) represent the most well-structured and organised means of communication apart from the oral languages spoken around the world. They are primarily used among individuals suffering from hearing loss and acoustic impairments via signs and gestures in the visual space. Similarly to spoken languages, SLs do not constitute a universal language but differ according to the areas and community groups from which they originate.  \nTo date, there is no official data confirming the current number of sign languages used in the world, yet at least 161 SLs have been documented [1] . The main distinctive features of SLs are the multimodality, simultaneity and iconicity of the communicative act. Indeed, the linguistic information is conveyed by means of visual and manual interactions to which the interlocutor needs to simultaneously pay attention. These are hand shapes and movements, together with oriented gestures, facial expressions and mouthing[2, 3] . Given the complex set of elements  \nAIxIA 2021, December 01–03, 2021, online  \n[Envelope-Open](Envelope-Open veronicajuliana.schmalz@kuleuven.be)[ veronicajuliana.schmalz@kuleuven.be](Envelope-Open veronicajuliana.schmalz@kuleuven.be) (V. J. Schmalz)  \nGLOBE https://github.com/VeroJulianaSchmalz (V. J. Schmalz)  \nOrcid 0000-0002-1636-6133 (V. J. Schmalz)  \n © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0) . CWPEURorkroceshopedings http://ceurISSN 1613-ws-0073.org CEUR Workshop Proceedings ([CEUR-WS.org](CEUR-WS.org))  \nthat must be taken into account when analysing SL use, in this project we will mainly focus on one-handed isolated static signs, generally performed with the signer’s dominant hand. More specifically, in our case we will be considering the letters of the LIS alphabet, one of the key elements to acquire when learning a sign language. The rest ofthe paper is organised as follows. Section 2 provides relevant details concerning the Italian Sign Language. A brief overview about the use of automatic recognition strategies in sign languages is presented in Section 3. Next, Section 4 describes the datasets taken into account for this project. In Section 5 we outline the tools and methodologies used for","cbCaicHXooksaaS9","https://ap.wps.com/l/cbCaicHXooksaaS9","pdf",2624947,1,13,"English","en",105,"# Introduction\n# The Italian Sign Language (LIS)","[{\"question\":\"What is the main goal of this project?\",\"answer\":\"The project aims to build a real-time automatic recognition system for the Italian Sign Language (LIS) alphabet letters in a human-computer interaction framework.\"},{\"question\":\"Which deep learning models and tools are used for recognition?\",\"answer\":\"The system uses two convolutional neural network architectures, CNN and VGG19, implemented for image and video recognition with Python’s Open Source Computer Vision (OpenCV) library.\"},{\"question\":\"What data and scope does the research focus on?\",\"answer\":\"The work tests performance using a recently acknowledged LIS and a newly released open-source dataset, focusing on single-handed isolated static signs of the LIS alphabet.\"}]","Real-time Italian Sign Language Recognition with Deep Learning | PDF",1787299032,33,{"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":87,"head_meta":89,"extra_data":91,"updated_unix":28},"real-time-italian-sign-language-recognition-with-deep-learning","",{"@graph":36,"@context":86},[37,54,69],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/real-time-italian-sign-language-recognition-with-deep-learning/134752/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-23","2026-08-21",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What is the main goal of this project?","Question",{"text":76,"@type":77},"The project aims to build a real-time automatic recognition system for the Italian Sign Language (LIS) alphabet letters in a human-computer interaction framework.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"Which deep learning models and tools are used for recognition?",{"text":81,"@type":77},"The system uses two convolutional neural network architectures, CNN and VGG19, implemented for image and video recognition with Python’s Open Source Computer Vision (OpenCV) library.",{"name":83,"@type":74,"acceptedAnswer":84},"What data and scope does the research focus on?",{"text":85,"@type":77},"The work tests performance using a recently acknowledged LIS and a newly released open-source dataset, focusing on single-handed isolated static signs of the LIS alphabet.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,136],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":46,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":46,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":46,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":46,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":46,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":46,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]