{"id":1232,"date":"2026-01-21T12:00:36","date_gmt":"2026-01-21T12:00:36","guid":{"rendered":"http:\/\/hria.utcluj.ro\/?page_id=1232"},"modified":"2026-06-15T12:51:54","modified_gmt":"2026-06-15T12:51:54","slug":"rezultate","status":"publish","type":"page","link":"https:\/\/hria.utcluj.ro\/en\/rezultate\/","title":{"rendered":"Results"},"content":{"rendered":"<div class=\"wp-block-query is-layout-flow wp-block-query-is-layout-flow\"><ul class=\"wp-block-post-template is-layout-flow wp-block-post-template-is-layout-flow\"><li class=\"wp-block-post post-1778 post type-post status-publish format-standard hentry category-rezultate\">\n<div class=\"has-text-align-right wp-block-post-date\"><time datetime=\"2026-03-09T16:22:02+00:00\">March 9, 2026<\/time><\/div>\n\n<h2 class=\"wp-block-post-title\"><a href=\"https:\/\/hria.utcluj.ro\/en\/perceptia-si-intelegerea-scenelor-3d-din-imagini-aeriene\/\" target=\"_self\" >Perception and understanding of 3D scenes from aerial images<\/a><\/h2>\n\n\n\n<div class=\"wp-block-post-excerpt\"><p class=\"wp-block-post-excerpt__excerpt\">The conducted research aims to create a unified framework for interpreting visual data captured by UAV platforms, moving from pixel-level processing to complex semantic and structural representations. Three-level perception architecture The system is hierarchically organized to transform raw data into informed decisions: Synthetic dataset ClaraVid To train models capable of handling\u2026 <\/p><\/div>\n\n\n<hr class=\"wp-block-separator has-css-opacity\"\/>\n\n<\/li><li class=\"wp-block-post post-1776 post type-post status-publish format-standard hentry category-rezultate\">\n<div class=\"has-text-align-right wp-block-post-date\"><time datetime=\"2026-03-09T10:46:54+00:00\">March 9, 2026<\/time><\/div>\n\n<h2 class=\"wp-block-post-title\"><a href=\"https:\/\/hria.utcluj.ro\/en\/nlp-si-speech-processing-de-la-grafuri-de-cunoastere-la-sinteza-vocala-si-securitatea-embedding-urilor\/\" target=\"_self\" >NLP and Speech Processing: from knowledge graphs to speech synthesis and embedding security<\/a><\/h2>\n\n\n\n<div class=\"wp-block-post-excerpt\"><p class=\"wp-block-post-excerpt__excerpt\">Advances in Natural Language and Speech Processing. Recent research within the Romanian AI Hub focuses on improving the efficiency of recommendation systems, the security of language models, and advancing speech synthesis technologies for the Romanian language. Knowledge Graph-based Recommender Systems (TRL 3). A recipe recommendation system is proposed, using a hybrid architecture\u2026 <\/p><\/div>\n\n\n<hr class=\"wp-block-separator has-css-opacity\"\/>\n\n<\/li><li class=\"wp-block-post post-1835 post type-post status-publish format-standard hentry category-rezultate\">\n<div class=\"has-text-align-right wp-block-post-date\"><time datetime=\"2026-03-09T10:35:00+00:00\">March 9, 2026<\/time><\/div>\n\n<h2 class=\"wp-block-post-title\"><a href=\"https:\/\/hria.utcluj.ro\/en\/modele-transformer-si-agentic-digital-twins-pentru-prognoza-si-managementul-energiei-distribuite\/\" target=\"_self\" >Transformer Models and Agentic Digital Twins for Distributed Energy Forecasting and Management<\/a><\/h2>\n\n\n\n<div class=\"wp-block-post-excerpt\"><p class=\"wp-block-post-excerpt__excerpt\">The research focuses on identifying AI-based solutions and Digital Twin concepts to address complex forecasting challenges in distributed energy networks (Smart Grids). Forecasting challenges and Digital Twin architecture. Representation-augmented Temporal Fusion Transformer (TFT) architecture. This hybrid approach learns stabilized temporal representations conditioned on structural information, providing a... <\/p><\/div>\n\n\n<hr class=\"wp-block-separator has-css-opacity\"\/>\n\n<\/li><li class=\"wp-block-post post-1798 post type-post status-publish format-standard hentry category-rezultate\">\n<div class=\"has-text-align-right wp-block-post-date\"><time datetime=\"2026-03-09T10:31:58+00:00\">March 9, 2026<\/time><\/div>\n\n<h2 class=\"wp-block-post-title\"><a href=\"https:\/\/hria.utcluj.ro\/en\/detectarea-obiectelor-spatiale-cu-inteligenta-artificiala\/\" target=\"_self\" >Detection of space objects using artificial intelligence<\/a><\/h2>\n\n\n\n<div class=\"wp-block-post-excerpt\"><p class=\"wp-block-post-excerpt__excerpt\">Monitoring outer space is becoming increasingly important in the context of the growing number of satellites and the risks associated with space debris. An AI-based approach is proposed for detecting and analyzing space objects using optical instruments. The main goal of this approach is the development of efficient methods for: The system is designed for\u2026 <\/p><\/div>\n\n\n<hr class=\"wp-block-separator has-css-opacity\"\/>\n\n<\/li><li class=\"wp-block-post post-1822 post type-post status-publish format-standard hentry category-rezultate\">\n<div class=\"has-text-align-right wp-block-post-date\"><time datetime=\"2026-03-09T09:52:00+00:00\">March 9, 2026<\/time><\/div>\n\n<h2 class=\"wp-block-post-title\"><a href=\"https:\/\/hria.utcluj.ro\/en\/sisteme-avansate-de-robotica-medicala-localizarea-athena-estimarea-fortei-sensorless-si-navigatie-dentara-markerless\/\" target=\"_self\" >Advanced medical robotics systems: ATHENA localization, sensorless force estimation, and markerless dental navigation<\/a><\/h2>\n\n\n\n<div class=\"wp-block-post-excerpt\"><p class=\"wp-block-post-excerpt__excerpt\">The research focuses on developing innovative solutions for minimally invasive surgery and robotic implantology, eliminating the need for complex hardware sensors through the use of advanced computer vision techniques. Automatic localization and positioning of the ATHENA robot. Sensorless force estimation in minimally invasive surgery. Markerless perception for navigation in dental implantology. <\/p><\/div>\n\n\n<hr class=\"wp-block-separator has-css-opacity\"\/>\n\n<\/li><li class=\"wp-block-post post-1733 post type-post status-publish format-standard hentry category-rezultate\">\n<div class=\"has-text-align-right wp-block-post-date\"><time datetime=\"2026-03-09T09:17:03+00:00\">March 9, 2026<\/time><\/div>\n\n<h2 class=\"wp-block-post-title\"><a href=\"https:\/\/hria.utcluj.ro\/en\/modele-multimodale-neuro-simbolice-image-captioning-si-kblam-in-domeniul-medical\/\" target=\"_self\" >Multimodal Neuro-Symbolic Models: Image Captioning and KBLaM in the Medical Domain<\/a><\/h2>\n\n\n\n<div class=\"wp-block-post-excerpt\"><p class=\"wp-block-post-excerpt__excerpt\">Medical Image Captioning: ImageHRM and ImageTRM Architectures The research focuses on developing advanced models for generating accurate descriptions of medical images, using hierarchical and recursive structures. ImageHRM (Hierarchical Reasoning Model) ImageTRM (Tiny Recursive Model) Transferable Knowledge Base Augmented Language Models (KBLaM) The portability of knowledge base-augmented language models across\u2026 <\/p><\/div>\n\n\n<hr class=\"wp-block-separator has-css-opacity\"\/>\n\n<\/li><li class=\"wp-block-post post-1790 post type-post status-publish format-standard hentry category-rezultate\">\n<div class=\"has-text-align-right wp-block-post-date\"><time datetime=\"2026-03-09T09:10:18+00:00\">March 9, 2026<\/time><\/div>\n\n<h2 class=\"wp-block-post-title\"><a href=\"https:\/\/hria.utcluj.ro\/en\/agrobots-inteligenta-artificiala-pentru-monitorizarea-culturilor-agricole-cu-roboti-mobili\/\" target=\"_self\" >AgroBots: Artificial Intelligence for monitoring agricultural crops using mobile robots<\/a><\/h2>\n\n\n\n<div class=\"wp-block-post-excerpt\"><p class=\"wp-block-post-excerpt__excerpt\">Artificial intelligence is used in agricultural environment monitoring through the integration of mobile robots and aerial imagery. The main goal is to develop automated solutions for crop analysis, with a focus on early disease detection and understanding plant structure. Modern agriculture requires efficient and scalable methods for monitoring crop health. The use of drones and mobile robots enables\u2026 <\/p><\/div>\n\n\n<hr class=\"wp-block-separator has-css-opacity\"\/>\n\n<\/li><li class=\"wp-block-post post-1726 post type-post status-publish format-standard hentry category-rezultate\">\n<div class=\"has-text-align-right wp-block-post-date\"><time datetime=\"2026-03-09T08:58:45+00:00\">March 9, 2026<\/time><\/div>\n\n<h2 class=\"wp-block-post-title\"><a href=\"https:\/\/hria.utcluj.ro\/en\/arhitecturi-agentice-si-modele-de-deep-learning-in-cadrul-romanian-ai-hospital\/\" target=\"_self\" >Romanian AI Hospital \u2013 agentic architectures and deep learning models<\/a><\/h2>\n\n\n\n<div class=\"wp-block-post-excerpt\"><p class=\"wp-block-post-excerpt__excerpt\">Agentic AI: Video Segmentation for Polyp Detection (Gastro Clinic) The implementation aims to optimize polyp detection through real-time video segmentation, using a colonoscopic agent based on SOTA (State-of-the-Art) architectures. Architecture and Methodology Performance and Validation Automatic Invoice Management &amp; Resident Support System The system integrates administrative document processing and academic support through neuro-symbolic methods and ontologies\u2026 <\/p><\/div>\n\n\n<hr class=\"wp-block-separator has-css-opacity\"\/>\n\n<\/li><li class=\"wp-block-post post-1815 post type-post status-publish format-standard hentry category-rezultate\">\n<div class=\"has-text-align-right wp-block-post-date\"><time datetime=\"2026-03-09T08:27:37+00:00\">March 9, 2026<\/time><\/div>\n\n<h2 class=\"wp-block-post-title\"><a href=\"https:\/\/hria.utcluj.ro\/en\/deep-learning-in-imagistica-medicala-segmentare-multimodala-si-diagnostic-asistat\/\" target=\"_self\" >Deep learning in medical imaging: multimodal segmentation and assisted diagnosis<\/a><\/h2>\n\n\n\n<div class=\"wp-block-post-excerpt\"><p class=\"wp-block-post-excerpt__excerpt\">Recent HRIA research, conducted in partnership with medical universities, aims to improve diagnostic accuracy through neural architectures optimized for various types of scans (CT, MRI, X-ray, OCT). Vascular Network Segmentation and Radiographic Analysis. Structural improvements are introduced to standard models to increase sensitivity in detecting fine anatomical structures: Angio-OCT (Retinal Networks): The\u2026 <\/p><\/div>\n\n\n<hr class=\"wp-block-separator has-css-opacity\"\/>\n\n<\/li><li class=\"wp-block-post post-1811 post type-post status-publish format-standard hentry category-rezultate\">\n<div class=\"has-text-align-right wp-block-post-date\"><time datetime=\"2026-03-09T07:58:20+00:00\">March 9, 2026<\/time><\/div>\n\n<h2 class=\"wp-block-post-title\"><a href=\"https:\/\/hria.utcluj.ro\/en\/clasificarea-si-monitorizarea-solului-din-imagini-satelitare\/\" target=\"_self\" >Soil classification and monitoring from satellite imagery<\/a><\/h2>\n\n\n\n<div class=\"wp-block-post-excerpt\"><p class=\"wp-block-post-excerpt__excerpt\">Processing satellite imagery using artificial intelligence offers new opportunities for environmental analysis and monitoring, especially in agriculture. This approach focuses on developing automated methods for soil classification and extracting relevant information from satellite data. Creation and expansion of datasets. A first essential step is the construction and improvement of\u2026 <\/p><\/div>\n\n\n<hr class=\"wp-block-separator has-css-opacity\"\/>\n\n<\/li><\/ul><\/div>","protected":false},"excerpt":{"rendered":"","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"neve_meta_sidebar":"","neve_meta_container":"","neve_meta_enable_content_width":"","neve_meta_content_width":0,"neve_meta_title_alignment":"","neve_meta_author_avatar":"","neve_post_elements_order":"","neve_meta_disable_header":"","neve_meta_disable_footer":"","neve_meta_disable_title":"on","_themeisle_gutenberg_block_has_review":false,"footnotes":""},"class_list":["post-1232","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/hria.utcluj.ro\/en\/wp-json\/wp\/v2\/pages\/1232","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hria.utcluj.ro\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/hria.utcluj.ro\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/hria.utcluj.ro\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/hria.utcluj.ro\/en\/wp-json\/wp\/v2\/comments?post=1232"}],"version-history":[{"count":11,"href":"https:\/\/hria.utcluj.ro\/en\/wp-json\/wp\/v2\/pages\/1232\/revisions"}],"predecessor-version":[{"id":1888,"href":"https:\/\/hria.utcluj.ro\/en\/wp-json\/wp\/v2\/pages\/1232\/revisions\/1888"}],"wp:attachment":[{"href":"https:\/\/hria.utcluj.ro\/en\/wp-json\/wp\/v2\/media?parent=1232"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}