Considering the substantial inaccuracies inherent in the traditional manual identification of ceramic categories and the issues associated with analyzing ceramics based on chemical or spectral features, which may lead to the destruction of ceramics, this paper introduces a novel provenance classification of archaeological ceramics which relies on microscopic features and an ensemble deep learning model, overcoming the time consuming and require costly equipment limitations of current standard methods, and without compromising the structural integrity and artistic value of ceramics. The proposed model includes the following: the construction of a dataset for ancient ceramic microscopic images, image preprocessing methods based on Gamma correction and CLAHE equalization algorithms, extraction of image features based on three deep learning architectures—VGG-16, Inception-v3 and GoogLeNet, and optimal fusion. This latter is based on stochastic gradient descent (SGD) algorithm, which allows optimal fitting of the fusion model parameters by freezing and unfreezing model layers. The experiments employ accuracy, precision, recall and F1 score criteria to offer a comprehensive of the classification outcomes. Under 5-fold cross-validation and independent testing, the proposed fusion-based model performed excellently after comparing above three typical deep learning model. The predictive results of the ensemble deep learning are very stable at about 0.9601, 0.9615, 0.9607 and 0.9583 in precision, recall, F1-score, and accuracy on the independent testing dataset, respectively. This indicates that our model is robust and reliable. Furthermore, we use correspondence analysis to explore the distribution of the ceramic microscopic images from different kilns. This method can be applied in the field of ceramic cultural relic identification, contributing to improved diagnostic accuracy and efficiency, and providing new ideas and methods for related research areas.
The ceramic lamps used to carry ancient Eastern civilization,but due to the backwardness of industrial production in modern society,the development of ceramic lamps has slightly stagnated.The cultural depth,excellent functionality,beauty of materials,abundance of decoration,skillful craftsmanship,and the combination of practicality and aesthetics of ceramic lighting fixtures inevitably bring them back to the public's perspective.This article will explore the artistic characteristics of ceramic lighting fixtures in five aspects,injecting new vitality into the design of ceramic lighting fixtures.
公元十至十三世纪之际,在我国北方地区相继建立了实力雄厚的辽金王朝.938年,后晋石敬瑭将燕云十六州割让于契丹辽国,从此大同成为辽国西南属地.1044年,辽兴宗升云州为西京大同府,自此大同成为辽五京之一.金灭辽后,袭辽制,仍称大同为西京.西京大同作为辽金两朝重要的都城,是当时政治经济文化中心之一.因此,这时期该地区的农牧经济、手工制作呈现出一派繁荣景象,而辉煌的瓷器制造业就是最为典型的案例.浑源窑、青瓷窑、怀仁窑引领雁北窑场,成为当时北中国重要的瓷器生产基地,而其生产的黑釉剔花瓷器因釉色乌黑晶莹,器型古朴素雅,纹饰豪放粗犷,备受时人的青睐,产品远销日本、高丽等国.本文以大同瓷窑的剔花瓷为研究对象,从大同瓷窑的发展、剔花瓷的装饰艺术以及这种技法的传承与影响做分析与探讨.
人物画作为传统陶瓷装饰表现的主要题材,深受人们的喜爱.陶瓷艺术家们把中国人物画的特点、审美意识和陶瓷工艺技法相融合,把人物为题材的作品运用文学性、叙事性、情节性绘画的表现方式在陶瓷绘画中呈现,使中国人物画在陶瓷上再现和升华,给陶瓷人物画作品赋予更高的艺术价值.泥与土的高温烧成工艺也让陶瓷相比于纸本绘画更具备了历史的保存性,成为人们喜爱收藏的佳品.因此,本文想通过传统陶瓷人物画的表现形式、工艺技法和其价值进行探究和阐述.
珐琅彩瓷绘制技艺,创始于康熙晚期,是参照铜胎画珐琅技法,嫁接到瓷胎上,创新的一种瓷器装饰技艺.是中国古代彩瓷工艺顶峰时期的产物,具有极高的美学价值和文化价值.当代大众审美与传统审美之间存在着巨大差异.珐琅彩作为传统工艺美术面临严峻的生存挑战.近年来,文创产业蓬勃发展,给珐琅彩瓷器绘制技艺带来了新的发展机遇.本文通过对珐琅彩瓷器文创品开发的创新思考,为珐琅彩瓷器绘制技艺的传承与发展提供参考.
