Longway Technologies digitizes cultural heritage, building 18 high-quality data sets covering the four main areas of ancient clerical painting, golden plaque, Oracle and calligraphy, covering the business week to nearly 3,000 years of modernity, providing full-link data support for AI enabling cultural heritage from high-level collection to intelligent interpretation.
From the interpretation of Oracle AI to the authentication of the authenticity of ancient paintings, from the restoration of the creation of artefacts to the understanding of the multimodular classical text, artificial intelligence is reshaping the paradigm of cultural heritage conservation and research.
The "Yin Chi Weinwoon" AI model, published by the Anyang Teacher Training Team in the Central College, has successfully been read in the 100-plus unsolved cassicles, with a record of 92% accuracy in the recognition of the caste characters. Nature 2025 notes that the large polymode model has advanced the casteography for a hundred years, and has increased the reading efficiency of non-textary historical material by 50 times.
So the GPT model, which combines pentex, seals, paper, and ink multi-dimensional features, is 95% accurate for the authenticity of Song Yuanguk’s paintings. Science 2025 studies show that AI has surpassed the level of senior expert experts in pentex microanalysis.
The proliferation model has achieved revolutionary breakthroughs in restoration of objects such as murals, scrolls, paints, etc. The "Digital Hole" project, published by the Dung Shun Institute, was launched by AI, which generated a restoration programme based on the context of the damaged area and has repaired over 200 murals.
The Great Norther "Agrass Model" is based on 1 billion words and text training to support automatic markers, break-ups, translations, physical identification. The Chinese Book Office "Cybernet" has been using AI to complete the automated proofing of the 24th History Four Books, increasing efficiency by a factor of 100. ACL 2025's best thesis focuses on the NLP in Cajakuhan.
The "Specific" AI system, published by the Union of West Indies, has an automatic classification of 88% of past generation skeletal schools, identifying 12 major categories such as the Qin Han Goo-Suk and the Ming-Sung. CVPR 2026 presents a print-to-check algorithm based on a focus mechanism, with over 90% accuracy for suspicious scrutinizing.
The retrospect "Goldstone OCR" model supports the recognition of the words Oracle, Golden Man, Tung, Tung, and Dhui, with a 96% single-word recognition. The digitized Chinese Monument and Tong Dynasty's tombstones are more than 20,000. In the ICDAR 2025 competition, AI exceeded the average of human experts in the task of writing the broken monuments.
The four main areas of deep-tilled clerical, golden plaque, Oracle and calligraphy are the construction of a full-link cultural data infrastructure from high-resolution digitization to AI smart reading
4K/8K super-high-intensity ancient paintings, scrolls, mural digitized images with multi-dimensional indications of age-breaking, author affiliation, style genre, stamped areas, etc., in cooperation with the 50+ Museum.
The Oracles, Gold Swords, Bronze Taction, High-level Data on Curtain Clips, supported the Ai-Clause Text Interpretation, Text Evolution Study, and Gold Identification.
The digitized data of the ingenious calligraphy truth, tablets, ink manuscripts, covering the five bodies of the Zenung Zhenji, supports font recognition, pen analysis, style migration.
Generations of engraving works, stamp images, print spectrum data, border notes, supporting the use of affixional recognition, etching style generation, seal authentication, etc.
In-depth cooperation with the 50+ cultural institutions such as the Palace of Manpower, the State of Gyborg, the Haut-Bog, the Dung Shun Institute and others to build networks for collecting authoritative cultural data
Joint archaeological, artistic, classical and literary experts to build a multidisciplinary and cross-cutting system of precision labelling to ensure the authority of cultural data
Strict compliance with laws and regulations on the protection of cultural objects, all data authorized for use, and solutions for compliance with digitalization of cultural objects
Self-study of the AIS-assisted label platform, supporting smart labels such as ancient text recognition, style classification, stamp extraction, 10 times more efficient
Four areas of focus for the digitized data base of cultural heritage: clerical drawings, goldstones, tablets, and stamped seals
Song Yuan Ching Chong has drawn a 4K/8K hyper-high-resolution digitized image with an abbreviated image of the age, author affiliation, genre classification, stamp recognition of the subject area.
High-resolution scanning data in the form of scrolls, scrolls, tablets, fan-scraps, including cross-references, stamp recognition, and apostasy.
The top-notch digital files of the walls of the temples of the temples of the Dung Shomong, Yong Lok Palace and the Fahai Temple, with signs of reading, age-breaking and damage assessment.
The true book is a spectrograph sample, which includes cross-touch microanalysis, stamp matching, paper age, ink composition, etc.
Disaggregated data by style styles such as plaza, clerical, pen, writing, boneless, etc., support style recognition and migration generation.
The ruins are the result of a high-level image of the top-level, single-word slitting, acoustic reading, a grouping of words, a time-speculation, covering the late generations of the merchants.
Queu Bronze Scroll (Kin) microscope and Zing data, with emulations, classification of instruments, time determinations, signs of clan.
Han Wei's monument, Tang Dynasty, Morcinary Carving and 3D scan data, including text recognition, book classification, and age-discounted signs.
Zhou Bronze Swords, Dragon Snacks, Fowl Snacks, etc., are disaggregated to support the development of the Tasty Evolving Study and the Ai style recognition.
Oracle is interpreted to distinguish the image by word from the typographical data, with cross-dimensional indications of words, words, words, words, etc.
The historical figures of the book-writing truths of Wang Xinxiang, Yan Jing, Su Xuan and Zhao Meng Xuan include book classification, pen analysis, style characterization.
The ancient tablets are well-developed, with high-level data, with multi-dimensional indications of the interpretation, the books, the times, the tablet owners, the authors, etc.
⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ , ⁇ ,
Ink, manuscript, cross-section, high-resolution data, with text, author, age, paper material labels.
Qin Han Goo and Ming Shik-sik are well-defined and contain generic classification, Zilong, Knife, and printed material.
The printed images, including official, private and bookmarks, contain printed reading, time, printing master, material, shape and representation.
The digitalized data of the generational print spectrum, such as the Ten-Clock Mountain Print, the Fai Hung Hall Print, contain print, text, genre, and time labels.
The engraving of border images and text against data supports the use of border text recognition, engraving analysis, author identification, etc.
JSON label structure showing four types of data: ancient drawings, Oracle, calligraphy, etching
Six typical AI applications based on the Langhui Cultural Art Dataset
Training in AI validation models based on authentic and false data, supporting the identification of antiquated paintings, the breakdown of the ages, and the attribution of authors, with an accuracy rate of over 95 per cent.
Automatic recognition and interpretation of ancient texts such as Oracle, Gin and Monuments using large multimodular models have increased efficiency 50 times.
The restoration technology based on the proliferation model, which automatically fills the damaged area, reduces the colour of the colour, and has been restored to 200 + murals.
AI-driven art style migration and generation, which leads to a change in the style of different schools of thought, and the creation of new works with traditional art styles.
The seals based on the attention mechanism are a matching algorithm, with an accuracy of over 90 per cent for suspected stamps, and support for automatic genre classification.
To build knowledge maps of cultural heritage to support interdisciplinary research and knowledge discovery in the fields of artistic history, ancient literature, archaeology, etc.
Common answers to questions about cultural and artistic data sets
The Longway Cultural Art Data Set covers four areas: ancient graphs, gold sculpture, oracles, and calligraphy; 18 core data sets. It includes ancient high-resolution images, scrolls, mural digital files, amphibious microscopes, gold placards, embroidery, brass strips, family-style writings, tablets, placards, seals, spectros, marginal notes, etc., covering the full time span from the close to 3000 years of modern times, totalling 1 million + cultural heritage images.
Data are collected in cooperation with the Royal Palace Museum, the National Museum, the Shanghai Museum, the Dung Shun Institute and other cultural institutions, and are publicly available as resources for the digitization of cultural heritage. All data are used with authorization, in strict compliance with the relevant laws and regulations, such as the Law on the Protection of Cultural Objects and the Copyright Act.
The training to support the AI-based model in the cultural field, which provides intellectual tools for the preservation, research and transmission of cultural heritage, has served many museums, colleges and research institutions.
The two-quality control system, "Experts for Cultural Objects + AI" is used. The joint archaeology, art history, ancient scripts and other multidisciplinary experts review the content of the labels, and the self-study of the AI-Auxiliary Tags platform conducts automated quality checks, such as format verification, consistency checks, etc.
Supports multiple delivery methods such as image formats (JPEG/PNG/TIFF/UCPRAW), label formats (JSON/XML/COCO/YOLO), knowledge spectrometry formats (RDF/OWL/N-Triples), three-dimensional data formats (OBJ/PLY/GLTF).
Contacting Langhui data experts to obtain complete CICA catalogues, test privileges and customised solutions