• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 64 matches

• 2021
• 
  Mateus Martin, José Fernando Oliveira, Elsa Silva, Reinaldo Morabito, Pedro Munari:
  Three-dimensional guillotine cutting problems with constrained patterns: MILP formulations and a bottom-up algorithm. Expert Syst. Appl. 168: 114257 (2021)
• 
  Haolin Liu, Anran Lin, Xiaoguang Han, Lei Yang, Yizhou Yu, Shuguang Cui:
  Refer-it-in-RGBD: A Bottom-up Approach for 3D Visual Grounding in RGBD Images. CoRR abs/2103.07894 (2021)
• 2020
• 
  Ziwei Li, Bo He, Weixing Feng:
  Evaluation of bottom-up and top-down mass spectrum identifications with different customized protein sequences databases. Bioinform. 36(4): 1030-1036 (2020)
• 
  Zhonghua Wu, Qingyi Tao, Guosheng Lin, Jianfei Cai:
  Exploring Bottom-Up and Top-Down Cues With Attentive Learning for Webly Supervised Object Detection. CVPR 2020: 12933-12942
• 
  Sachin Raja, Ajoy Mondal, C. V. Jawahar:
  Table Structure Recognition Using Top-Down and Bottom-Up Cues. ECCV (28) 2020: 70-86
• 
  G. Anthony Giannoumis, Wondwossen Mulualem Beyene:
  Cultural Inclusion and Access to Technology: Bottom-Up Perspectives on Copyright Law and Policy in Norway. HCI (9) 2020: 341-355
• 
  Zhonghua Wu, Qingyi Tao, Guosheng Lin, Jianfei Cai:
  Exploring Bottom-up and Top-down Cues with Attentive Learning for Webly Supervised Object Detection. CoRR abs/2003.09790 (2020)
• 
  Sachin Raja, Ajoy Mondal, C. V. Jawahar:
  Table Structure Recognition using Top-Down and Bottom-Up Cues. CoRR abs/2010.04565 (2020)
• 2019
• 
  Pablo Fontoura, Jean-Marie Schaeffer, Michel Menu:
  The vision and interpretation of paintings: bottom-up visual processes, top-down culturally informed attention, and aesthetic experience. ETRA 2019: 51:1-51:3
• 
  Lucia Della Spina, Claudia Giorno, Ruggiero Galati Casmiro:
  Bottom-Up Processes for Culture-Led Urban Regeneration Scenarios. ICCSA (4) 2019: 93-107
• 
  Luckeciano Carvalho Melo, Marcos Ricardo Omena Albuquerque Máximo, Adilson Marques da Cunha:
  Bottom-Up Meta-Policy Search. CoRR abs/1910.10232 (2019)
• 2018
• 
  Miguel A. Barcelona, Laura García-Borgoñón, María José Escalona Cuaresma, Isabel M. Ramos:
  CBG-Framework: A bottom-up model-based approach for Collaborative Business Process Management. Comput. Ind. 102: 1-13 (2018)
• 
  Nevrez Imamoglu, Wataru Shimoda, Chi Zhang, Yuming Fang, Asako Kanezaki, Keiji Yanai, Yoshifumi Nishida:
  An integration of bottom-up and top-down salient cues on RGB-D data: saliency from objectness versus non-objectness. Signal Image Video Process. 12(2): 307-314 (2018)
• 
  Ron C. Li, Jason K. Wang, Christopher Sharp, Jonathan H. Chen:
  A "bottom up" data driven approach to curating electronic order sets. AMIA 2018
• 
  Guo Freeman, Shaowen Bardzell, Jeffrey Bardzell:
  Bottom-Up Imaginaries: The Cultural-Technical Practice of Inventing Regional Advantage through IT R&D. CHI 2018: 325
• 
  Ting Guo, Rundong Cui, Xiaoran Qin, Yongtao Wang, Zhi Tang:
  Bottom-up/Top-down Geometric Object Reconstruction with CNN Classification for Mobile Education. PG (Short Papers and Posters) 2018: 13-16
• 
  Nevrez Imamoglu, Wataru Shimoda, Chi Zhang, Yuming Fang, Asako Kanezaki, Keiji Yanai, Yoshifumi Nishida:
  An Integration of Bottom-up and Top-Down Salient Cues on RGB-D Data: Saliency from Objectness vs. Non-Objectness. CoRR abs/1807.01532 (2018)
• 2017
• 
  Nathaniel Blanco, Vladimir M. Sloutsky:
  Bottom-up attentional cueing in category learning in children. CogSci 2017
• 
  Anirban Roy, Sinisa Todorovic:
  Combining Bottom-Up, Top-Down, and Smoothness Cues for Weakly Supervised Image Segmentation. CVPR 2017: 7282-7291
• 
  Qibin Hou, Daniela Massiceti, Puneet Kumar Dokania, Yunchao Wei, Ming-Ming Cheng, Philip H. S. Torr:
  Bottom-Up Top-Down Cues for Weakly-Supervised Semantic Segmentation. EMMCVPR 2017: 263-277
• 
  Alejandro Gabriel Villanueva Zacarias, Laura Kassner, Bernhard Mitschang:
  Exploring Text Classification Configurations - A Bottom-up Approach to Customize Text Classifiers based on the Visualization of Performance. ICEIS (1) 2017: 504-511
• 2016
• 
  Rafael Arrais, Miguel Oliveira, Cesar Toscano, Germano Veiga:
  A Hybrid Top-Down Bottom-Up Approach for the Detection of Cuboid Shaped Objects. ICIAR 2016: 512-520
• 
  Sofoklis Kakouros, Joris Pelemans, Lyan Verwimp, Patrick Wambacq, Okko Räsänen:
  Analyzing the Contribution of Top-Down Lexical and Bottom-Up Acoustic Cues in the Detection of Sentence Prominence. INTERSPEECH 2016: 1074-1078
• 2015
• 
  Donald R. Musgrove, Lynn E. Eberly, Bonnie Klimes-Dougan, Zeynep Basgoze, Kathleen M. Thomas, Bryon A. Mueller, Alaa Houri, Kelvin O. Lim, Kathryn R. Cullen:
  Impaired Bottom-Up Effective Connectivity Between Amygdala and Subgenual Anterior Cingulate Cortex in Unmedicated Adolescents with Major Depression: Results from a Dynamic Causal Modeling Analysis. Brain Connect. 5(10): 608-619 (2015)
• 
  Ching Lik Teo, Cornelia Fermüller, Yiannis Aloimonos:
  A Gestaltist approach to contour-based object recognition: Combining bottom-up and top-down cues. Int. J. Robotics Res. 34(4-5): 627-652 (2015)
• 
  Tian Chen, Hongming Cai, Boyi Xu, Fenglin Bu:
  A Bottom-Up Approach for BOM Generation and Its Application in Mass Customization. ICEBE 2015: 347-353
• 2014
• 
  Chirag I. Patel, Sanjay Garg, Tanish Zaveri, Asim Banerjee:
  Top-Down and Bottom-Up Cues Based Moving Object Detection for Varied Background Video Sequences. Adv. Multim. 2014: 879070:1-879070:20 (2014)
• 
  André Klapper, Richard Ramsey, Daniël H. J. Wigboldus, Emily S. Cross:
  The Control of Automatic Imitation Based on Bottom-Up and Top-Down Cues to Animacy: Insights from Brain and Behavior. J. Cogn. Neurosci. 26(11): 2503-2513 (2014)
• 
  Davor Capalija, Tarek S. Abdelrahman:
  Tile-based bottom-up compilation of custom mesh-of-functional-units FPGA overlays. FPL 2014: 1-8
• 
  Takayoshi Yamashita, Taro Watasue:
  Hand posture recognition based on bottom-up structured deep convolutional neural network with curriculum learning. ICIP 2014: 853-857

skipping 34 more matches