Reference: | 一、中文文獻 1. 王宇慶、劉維亞、王勇(2008)。「一種基於局部變異和結構相似度的圖像質量評價方法」,《光電子,激光》,第11期,頁1546-1553。 2. 任大勇、賈振紅、楊傑(2019)。「結合位圖切割和區域合併的彩色圖像分割」,《計算機工程與應用》,55(2),頁162-167。 3. 安衛超、閻婷、張楠、張彬、相洁、曹銳、王彬(2021)。「病理圖像紋理分析在胃癌MSI預測中的應用研究」,《計算機工程與應用》,57(24),頁205-211。 4. 李偉斌、馬洪林、易賢、趙凡、李維浩(2019)。「基於色彩空間變換的彩色圖像分割法」,《計算機工程與應用》,55(9),頁162-167。 5. 胡毅(2015)。「米勒《拾穗》賞析」,《時代文學(下半月)》,第7期,頁75-75。 6. 郭麗、黃元元、楊靜宇(2004)。「用分塊圖像特徵進行商標圖像檢索」,《計算機輔助設計與圖形學學報》,第7期,頁968-972。 7. 黃衍翠(2010)。「從《日出·印象》談印象派油畫之美」,《時代文學(上半月)》,第3期,頁229-231。 8. 楊賢藝(2006)。「論印象派繪畫的藝術特色」,《藝術教育》,第4期,頁94-95。 9. 廖國紅、齊軍、黃光林(2007)。「基於支持向量機方法的醫學圖像分割」,《計算機工程與應用》,43(29),頁217-219。 10. 龔如森 (2016)。「西班牙藝術夜空裡的星光-寫實主義的委拉斯蓋茲與浪漫主義的哥雅」,中國文化大學藝術學院美術學系學系碩士論文。 二、英文文獻 1. Alara* H., and Fernandezb P. (2021) “Classifying mosquito presence and genera using median and interquartile values from 26-filter wingbeat acoustic properties.”, Procedia Computer Science, 193, 453-463. 2. Agrawal S., Verma N., Tamrakar P., and Sircar P. (2011) “Content based color image classification using SVM.”, IEEE International Conference on Information Technology, New Generations, 1090 – 1094. 3. Agarwal S., Karnick H., Pant N., and Patel U. (2015) “Genre and style-based painting classification.”, IEEE Winter Conference on Applications of Computer Vision, 588 – 594. 4. Barni M., Pelagotti A., and Piva A. (2005) “Image processing for the analysis and conservation of paintings: opportunities and challenges.”, IEEE Signal Process Magazine, 22, 141–144. 5. Cheng Y. C. and Chen S. Y. (2001) “Image classification using color, texture and regions.”, Image and Vision Computing, 21, 759-776. 6. Ji M., and Yuyu Y. (2019) “Dimension reduction of image deep feature using PCA.”, Journal of Visual Communication and Image Representation, 63, 102578. 7. Junhua C. and Jing L. (2012) “Research on color image classification based on HSV color space.”, 2012 Second International Conference on Instrumentation, Measurement, Computer, Communication and Control, 944 – 947. 8. Ke, G., Meng, Q., Finley, T., Wang, T., Chen, W., Ma, W., Ye, Q., Liu, T.-Y. (2017) “Lightgbm: A highly efficient gradient boosting decision tree.”, Advances in neural information processing systems 2017, 30. 9. LOWE D. (2004) “Distinctive image features from scale-invariant key points.”, International Journal of Computer Vision, 60(2), 91–110. 10. Ogunleye A. and Wang, Q. G. (2019) “XGBoost model for chronic kidney disease diagnosis.”, IEEE ACM Transactions on Computational Biology and Bioinformatics, 17(6), 2131 – 2140. 11. Robert M., Shanmugam K., and Dinstein I. (1973) “Textural features for image classification.”, IEEE Transactions on Systems, Man and Cybernetics, SMC-3(6), 610 – 621. 12. Süsstrunk, S., Buckley, R., and Swen, S. (1999) “Standard RGB color spaces.”, Color and Imaging Conference, 127–134. 13. Tian, D. P. (2013) “A review on image feature extraction and representation techniques.”, International Journal of Multimedia and Ubiquitous Engineering, 8, 385–396. 14. Wang, X. and Nicolas D. (2009) “GLCM textured based fractal method for evaluating fabric surface roughness.”, Canadian Conference on Electrical and Computer Engineering, 104 – 107. 15. Xin M. and Wang Y. (2019) “Research on image classification model based on deep convolution neural network.”, EURASIP Journal on Image and Video Processing, 40. |