標題: Titlebook: Data Analytics for Cultural Heritage; Current Trends and C Abdelhak Belhi,Abdelaziz Bouras,Abdul Hamid Sadka Book 2021 The Editor(s) (if ap [打印本頁] 作者: dentin 時間: 2025-3-21 18:17
書目名稱Data Analytics for Cultural Heritage影響因子(影響力)
書目名稱Data Analytics for Cultural Heritage影響因子(影響力)學科排名
書目名稱Data Analytics for Cultural Heritage網(wǎng)絡(luò)公開度
書目名稱Data Analytics for Cultural Heritage網(wǎng)絡(luò)公開度學科排名
書目名稱Data Analytics for Cultural Heritage被引頻次
書目名稱Data Analytics for Cultural Heritage被引頻次學科排名
書目名稱Data Analytics for Cultural Heritage年度引用
書目名稱Data Analytics for Cultural Heritage年度引用學科排名
書目名稱Data Analytics for Cultural Heritage讀者反饋
書目名稱Data Analytics for Cultural Heritage讀者反饋學科排名
作者: Bmd955 時間: 2025-3-21 20:43
Visual Classification of Intangible Cultural Heritage Images in the Mekong Delta,VM models using automated deep learning of invariant features outperform SVM models trained on handcrafted features. Fine-tuning Inception-v3, Xception, and two non-linear SVM models learned from Inception-v3 and Xception features achieve 60.46%, 61.54%, 61.54%, and 62.89% accuracy, respectively. We作者: 他日關(guān)稅重重 時間: 2025-3-22 02:10 作者: frenzy 時間: 2025-3-22 05:09
Crowd Source Framework for Indian Digital Heritage Space,ies, and efficient AI and Ml algorithms have made it possible to address challenges of big data storage and analytics. We present our work towards building a crowd source platform for data collection, data preprocessing, classification, storage, and query-based retrieval. The platform is used for up作者: 委屈 時間: 2025-3-22 10:07 作者: Robust 時間: 2025-3-22 15:28
Aesthetical Issues with Stochastic Evaluation,ndscape-impact analysis, (b) insights into the expression forms of the examined artists and historical periods, and finally (c) evidence that can be used in the search of the originality of an artwork of disputed authorship.作者: Robust 時間: 2025-3-22 19:59 作者: 易碎 時間: 2025-3-22 21:25 作者: 抵制 時間: 2025-3-23 01:38 作者: miscreant 時間: 2025-3-23 08:00 作者: cocoon 時間: 2025-3-23 13:24 作者: audiologist 時間: 2025-3-23 15:57 作者: 銼屑 時間: 2025-3-23 20:48 作者: 獨裁政府 時間: 2025-3-24 00:14 作者: 即席 時間: 2025-3-24 05:17
NoisyArt: Exploiting the Noisy Web for Zero-shot Classification and Artwork Instance Recognition,ly-supervised classes, with a subset of 200 verified test images. Candidate artworks are identified using publicly available metadata repositories, and images are automatically acquired using search engines. Textual description and other information are provided for each artwork and artist, enabling作者: GENRE 時間: 2025-3-24 08:29
Cultural Heritage Image Classification,ication can be particularly challenging due to a high number of different image categories, feature variability, and the need for high reliability. Recent research shows that various machine learning techniques can be utilized for image classification purposes and that algorithms such as artificial 作者: defibrillator 時間: 2025-3-24 12:01 作者: ABASH 時間: 2025-3-24 18:15 作者: 熄滅 時間: 2025-3-24 20:13 作者: 我說不重要 時間: 2025-3-25 01:17
Crowd Source Framework for Indian Digital Heritage Space, are recognized by UNESCO. We need to preserve the information relevant to the sites in terms of history, art, culture, materials, architecture styles, and their role in the socioeconomic growth. These sites are of interest and value to architects, historians, and tourists for various levels of expl作者: 易于出錯 時間: 2025-3-25 06:41 作者: 離開就切除 時間: 2025-3-25 09:55
Aesthetical Issues with Stochastic Evaluation,gy based on stochastic mathematics is applied for the quantification of aesthetic attributes of paintings and landscapes. The paintings analyzed include Da Vinci, Pablo Picasso, and various other celebrated paintings from 1250?AD to modern times. In regard to landscapes, the analysis focuses on the 作者: lipoatrophy 時間: 2025-3-25 15:38
3D Visual Interaction for Cultural Heritage Sector,f heritage curation institutions and research is to implement user-friendly 3D visual interaction system to museums visitors..In this chapter, we firstly reviewed human-computer interaction techniques used in the cultural heritage sector, followed by details of hand gesture recognition applications 作者: CLAIM 時間: 2025-3-25 15:51 作者: CRUMB 時間: 2025-3-25 23:39 作者: chronicle 時間: 2025-3-26 02:57
Book 2021the cultural heritage digitization process. Particular focus is placed on improvements to the data acquisition stage, as well as the data enrichment and curation stages, using advanced artificial intelligence techniques and tools. An emphasis is placed on recent applications related to deep learning作者: 種類 時間: 2025-3-26 04:20 作者: Delude 時間: 2025-3-26 10:53 作者: 鉤針織物 時間: 2025-3-26 12:48 作者: Popcorn 時間: 2025-3-26 19:17 作者: expdient 時間: 2025-3-26 23:52
https://doi.org/10.1057/9781137302823uated in terms of user’s experience. The evaluation results showed the effectiveness of the proposed framework in offering a high-quality visual experience with a speedy response time of the interaction system.作者: 圓錐體 時間: 2025-3-27 01:26 作者: Crater 時間: 2025-3-27 09:17
NoisyArt: Exploiting the Noisy Web for Zero-shot Classification and Artwork Instance Recognition,iments demonstrate the benefits and limitations of this kind of approaches in the challenging setting of data scarcity and noisy labels for the set of seen classes. This chapter combines and extends our ongoing work on . dataset.作者: terazosin 時間: 2025-3-27 12:53 作者: 輕率看法 時間: 2025-3-27 14:02 作者: incontinence 時間: 2025-3-27 20:29 作者: Insubordinate 時間: 2025-3-27 22:25
challenges of improving data acquisition, enrichment and ma.This book considers the challenges related to the effective implementation of artificial intelligence (AI) and machine learning (ML) technologies to the cultural heritage digitization process. Particular focus is placed on improvements to 作者: Chivalrous 時間: 2025-3-28 04:00 作者: chance 時間: 2025-3-28 07:32
Early Modern Literature in Historyication can be particularly challenging due to a high number of different image categories, feature variability, and the need for high reliability. Recent research shows that various machine learning techniques can be utilized for image classification purposes and that algorithms such as artificial 作者: lipoatrophy 時間: 2025-3-28 10:46
‘An unnecessary flood of words’?ral heritage classification relies on the classification of asset images regarding a certain task such as type, artist, genre, style identification, etc. CH classification is challenging as various CH asset images have similar colors, textures, and shapes. In this chapter, the aim is to study and ev作者: Carminative 時間: 2025-3-28 18:26
‘An unnecessary flood of words’?ataset of 17 ICH categories and manually annotate them. We start with fine-tuning recent pre-trained deep learning models such as VGG19, ResNet50, Inception-v3, and Xception for classifying our own dataset. Followed which, we propose to train support vector machine (SVM) models using many popular vi作者: Allege 時間: 2025-3-28 20:40 作者: 移動 時間: 2025-3-29 01:46
‘An unnecessary flood of words’? are recognized by UNESCO. We need to preserve the information relevant to the sites in terms of history, art, culture, materials, architecture styles, and their role in the socioeconomic growth. These sites are of interest and value to architects, historians, and tourists for various levels of expl作者: 百靈鳥 時間: 2025-3-29 04:28 作者: 業(yè)余愛好者 時間: 2025-3-29 11:13
Sabrina P. Ramet,Ola Listhaug,Albert Simkusgy based on stochastic mathematics is applied for the quantification of aesthetic attributes of paintings and landscapes. The paintings analyzed include Da Vinci, Pablo Picasso, and various other celebrated paintings from 1250?AD to modern times. In regard to landscapes, the analysis focuses on the 作者: 舔食 時間: 2025-3-29 15:14 作者: 相反放置 時間: 2025-3-29 17:14
Understanding the Ohrid Framework Agreementn visual arts is to find similarity relationships among paintings of different artists and painting schools. To help art historians better understand visual arts, this chapter presents a framework for . in digital painting datasets. The proposed framework is based, on one hand, on a deep convolution作者: 得體 時間: 2025-3-29 19:49 作者: CYN 時間: 2025-3-30 01:21 作者: 缺乏 時間: 2025-3-30 05:40 作者: biosphere 時間: 2025-3-30 10:48
