Myrberg C.; Wiberg N.: Screen vs. Paper: what is the difference for reading and learning?
Insights, 28 (2015), 49–54.
Patel C.: Sustainable ecosystems: enabled by supply demand management, in Int. Conf. on Distributed Computing and Networking (ICDCN 2011), Bangalore, India, 2011, 12–28.
et al. METIS: a multi-faceted hybrid book learning platform, in The 16th ACM Symp. on Document Engineering (DocEng 2016), Vienna, Austria, 2016, 31–34.
et al. To print or not to print: Hybrid learning with METIS learning platform, in The 7th ACM SIGCHI Symp. on Engineering Interactive Computing Systems (EICS 2015), Duisburg, Germany, 2015, 206–215.
Vernica R.; Damera Venkata N.: AERO: an extensible framework for adaptive web layout synthesis in The 2015 ACM Symp. on Document Engineering (DocEng 2015), Lausanne, Switzerland, 2015, 187–190.
Liu L.; Koutrika G.; Wu S.: LearningAssistant: a novel learning resource recommendation system in The 31st IEEE Int. Conf. on Data Engineering (ICDE 2015), Seoul, Korea, 2015, 1424–1427.
Wang S.; Liu L.: Prerequisite concept maps extraction for automatic assessment in The LILE Workshop in 25th Int. World Wide Web Conf. (WWW 2016), Montreal Canada, 2016, 519–521.
Rui Y.; Huang T.S.: Image retrieval: current techniques, promising directions, and open issues. J. Vis. Commun. Image Represent., 10 (1999), 39–62.
Swets D.L.; Weng J.J.: Using discriminant eigenfeatures for image retrieval. IEEE Trans. Pattern. Anal. Mach. Intell., 18 (1996), 831–836.
Gudivada V.N.; Raghavan V.V.: Content based image retrieval systems. Computer, 28 (1995), 18–22.
Schmid C.; Mohr R.: Local gray value invariants for image retrieval. IEEE Trans. Pattern Anal. Mach. Intell., 19 (1997), 530–534.
Lawrence S.R.; Giles C.L.: Meta search engine. US Patent 6,999,959, February 14, 2006.
Smeulders A.W.; Worring M.; Santini S.; Gupta A.; Jain R.: Content-based image retrieval at the end of the early years. IEEE Trans. Pattern Anal. Mach. Intell., 22 (2000), 1349–1380.
Yang M.; Kpalma K.; Joseph R.: A survey of shape feature extraction techniques, in Pattern Recognition Techniques, Technology and Applications, InTech, 2008, 43–90.
Deb S.; Zhang Y.: An overview of content-based image retrieval techniques, in The 18th Int. Conf. on Advanced Information Networking and Applications (AINA 2004), Fukuoka, Japan, 2004, 59–64.
Giacinto G.: A nearest-neighbor approach to relevance feedback in content based image retrieval, in The 6th ACM Int. Conf. on Image and Video Retrieval, Amsterdam, The Netherlands, 2007, 456–463.
Csurka G.; Dance C.; Fan L.; Willamowski J.; Bray C.: Visual categorization with bags of keypoints, in The workshop on Statistical Learning in Computer Vision, ECCV, Prague, 2004, 1–22.
Lowe D. G.: Object recognition from local scale-invariant features, in The 7th IEEE Int. Conf. on Computer Vision (ICCV), Kerkyra, Greece, 1999, vol. 2, pp. 1150–1157.
MacQueen J.: Some methods for classification and analysis of multivariate observations, in The 5th Berkeley Symp. on Mathematical Statistics and Probability, Oakland, CA, USA, 1967, vol. 1, no. 14, pp. 281–297.
Dubois E.; Pathak A.: Reduction of bleed-through in scanned manuscript documents, in IS&T Image Processing, Image Quality, Image Capture Systems Conf., Montreal, Canada, 2001, 177–180.
Safari R.; Narasimhamurthi N.; Shridhar M.; Ahmadi M.: Form registration: a computer vision approach, in IEEE Int. Conf. on Document Analysis and Recognition (ICDAR), Ulm, Germany, 1997, vol. 2, pp. 758–761.
Mao J.; Mohiuddin K.: Form dropout using distance transformation, in IEEE Int. Conf. on Image Processing (ICIP), Washington, DC, USA, 1995, vol. 3, pp. 328–331.
Ye M.; Bern M.; Goldberg D.: Document image matching and annotation lifting, in IEEE Int. Conf. on Document Analysis and Recognition (ICDAR), Seattle, WA, USA, 2001, 753–760.
Isgro F.; Pilu M.: A fast and robust image registration method based on an early consensus paradigm. Pattern Recognit. Lett., 25 (2004), 943–954.
Yang J.; Blum R.S.; Williams J.P.; Sun Y.; Xu C.: Non-rigid image registration using geometric features and local salient region features, in IEEE Computer Society Conf. on Computer Vision and Pattern Recognition (CVPR), New York, NY, USA, 2006, vol. 1, pp. 825–832.
Lei Y.; Fan J.; Liu J.: A multi-scale approach to extract meaningful annotations from document images, in IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), Shanghai, China, 2016, 1951–1955.