• 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 253 matches

• 2021
• 
  Muammer Turkoglu:
  COVIDetectioNet: COVID-19 diagnosis system based on X-ray images using features selected from pre-learned deep features ensemble. Appl. Intell. 51(3): 1213-1226 (2021)
• 
  Liton Devnath, Suhuai Luo, Peter Summons, Dadong Wang:
  Automated detection of pneumoconiosis with multilevel deep features learned from chest X-Ray radiographs. Comput. Biol. Medicine 129: 104125 (2021)
• 
  Yishu Liu, Guifang Fu:
  Emotion recognition by deeply learned multi-channel textual and EEG features. Future Gener. Comput. Syst. 119: 1-6 (2021)
• 
  Zichao Zhang, Torsten Sattler, Davide Scaramuzza:
  Reference Pose Generation for Long-term Visual Localization via Learned Features and View Synthesis. Int. J. Comput. Vis. 129(4): 821-844 (2021)
• 
  Justin Tomasi, Brandon Wagstaff, Steven L. Waslander, Jonathan Kelly:
  Learned Camera Gain and Exposure Control for Improved Visual Feature Detection and Matching. IEEE Robotics Autom. Lett. 6(2): 2028-2035 (2021)
• 
  Marek Dobranský, Tomás Skopal:
  On Fusion of Learned and Designed Features for Video Data Analytics. MMM (2) 2021: 268-280
• 
  Justin Tomasi, Brandon Wagstaff, Steven L. Waslander, Jonathan Kelly:
  Learned Camera Gain and Exposure Control for Improved Visual Feature Detection and Matching. CoRR abs/2102.04341 (2021)
• 
  Jie Ren, Die Zhang, Yisen Wang, Lu Chen, Zhanpeng Zhou, Xu Cheng, Xin Wang, Yiting Chen, Jie Shi, Quanshi Zhang:
  Game-theoretic Understanding of Adversarially Learned Features. CoRR abs/2103.07364 (2021)
• 
  Hudson M. S. Bruno, Esther Luna Colombini:
  A comparative evaluation of learned feature descriptors on hybrid monocular visual SLAM methods. CoRR abs/2104.00085 (2021)
• 2020
• 
  Haowen Deng:
  Learned 3D Local Features for Rigid Pose Estimation on Point Clouds. Technical University of Munich, Germany, 2020
• 
  Mustaqeem, Muhammad Sajjad, Soonil Kwon:
  Clustering-Based Speech Emotion Recognition by Incorporating Learned Features and Deep BiLSTM. IEEE Access 8: 79861-79875 (2020)
• 
  Qingyang Ding, Siyu Hou, Songpeng Zu, Yonghui Zhang, Shao Li:
  VISAR: an interactive tool for dissecting chemical features learned by deep neural network QSAR models. Bioinform. 36(11): 3610-3612 (2020)
• 
  Shuo Zhuang, Ping Wang, Boran Jiang, Maosong Li:
  Learned features of leaf phenotype to monitor maize water status in the fields. Comput. Electron. Agric. 172: 105347 (2020)
• 
  Hui Wang, Guohui Yuan, Xuegong Zhao, Lingbing Peng, Zhuoran Wang, Yanmin He, Chao Qu, Zhenming Peng:
  Hard exudate detection based on deep model learned information and multi-feature joint representation for diabetic retinopathy screening. Comput. Methods Programs Biomed. 191: 105398 (2020)
• 
  Sufang Liu, Lei Shi, Simian Liu, Chuan Wang, Chulin Chen:
  City space type recognition by leveraging deeply-learned topological features. Future Gener. Comput. Syst. 112: 624-629 (2020)
• 
  Jorge García-González, Juan Miguel Ortiz-de-Lazcano-Lobato, Rafael M. Luque-Baena, Ezequiel López-Rubio:
  Background subtraction by probabilistic modeling of patch features learned by deep autoencoders. Integr. Comput. Aided Eng. 27(3): 253-265 (2020)
• 
  C. Chahla, Hichem Snoussi, Fahed Abdallah, Fadi Dornaika:
  Learned versus Handcrafted Features for Person Re-identification. Int. J. Pattern Recognit. Artif. Intell. 34(4): 2055009:1-2055009:19 (2020)
• 
  Rolf Ploetzner, Sandra Berney, Mireille Bétrancourt:
  A review of learning demands in instructional animations: The educational effectiveness of animations unfolds if the features of change need to be learned. J. Comput. Assist. Learn. 36(6): 838-860 (2020)
• 
  Fernando Giner, Enrique Amigó, Felisa Verdejo:
  Integrating learned and explicit document features for reputation monitoring in social media. Knowl. Inf. Syst. 62(3): 951-985 (2020)
• 
  Ilaria Patrini, Michela Ruperti, Sara Moccia, Leonardo S. Mattos, Emanuele Frontoni, Elena De Momi:
  Transfer learning for informative-frame selection in laryngoscopic videos through learned features. Medical Biol. Eng. Comput. 58(6): 1225-1238 (2020)
• 
  Faheem Akhtar, Jianqiang Li, Yan Pei, Azhar Imran, Asif Rajput, Muhammad Azeem, Bo Liu:
  Diagnosis of large-for-gestational-age infants using a semi-supervised feature learned from expert and data. Multim. Tools Appl. 79(45-46): 34047-34077 (2020)
• 
  Pamela Johnston, Eyad Elyan, Chrisina Jayne:
  Video tampering localisation using features learned from authentic content. Neural Comput. Appl. 32(16): 12243-12257 (2020)
• 
  Fengyuan Wang, Chi Zhang, Shenghui Chen, Guode Ying, Jianhua Lv:
  Engineering Hand-designed and Deeply-learned features for person Re-identification. Pattern Recognit. Lett. 130: 293-298 (2020)
• 
  Xianxian Zeng, Xiaodong Wang, Kairui Chen, Dong Li, Yun Zhang, Kin-Man Lam:
  Deeply learned pore-scale facial features with a large pore-to-pore correspondences dataset. Pattern Recognit. Lett. 129: 247-254 (2020)
• 
  Essam Abdellatef, Eman M. Omran, Randa F. Soliman, Nabil A. Ismail, Salah Eldin S. E. Abd Elrahman, Khalid N. Ismail, Mohamed Rihan, Fathi E. Abd El-Samie, Ayman A. Eisa:
  Fusion of deep-learned and hand-crafted features for cancelable recognition systems. Soft Comput. 24(20): 15189-15208 (2020)
• 
  Yang Liu, Ajay Kumar:
  Contactless Palmprint Identification Using Deeply Learned Residual Features. IEEE Trans. Biom. Behav. Identity Sci. 2(2): 172-181 (2020)
• 
  Wenzheng Chen, Fangyin Wei, Kiriakos N. Kutulakos, Szymon Rusinkiewicz, Felix Heide:
  Learned feature embeddings for non-line-of-sight imaging and recognition. ACM Trans. Graph. 39(6): 230:1-230:18 (2020)
• 
  Sanghoon Lee, Colton Farley, Simon Shim, Wook-Sung Yoo, Yanjun Zhao, Wookjin Choi:
  Unsupervised Learning of Deep-Learned Features from Breast Cancer Images. BIBE 2020: 740-745
• 
  Sungyong Baik, Hyo Jin Kim, Tianwei Shen, Eddy Ilg, Kyoung Mu Lee, Christopher Sweeney:
  Domain Adaptation of Learned Featuresfor Visual Localization. BMVC 2020
• 
  Runsen Feng, Yaojun Wu, Zongyu Guo, Zhizheng Zhang, Zhibo Chen:
  Learned Video Compression with Feature-level Residuals. CVPR Workshops 2020: 529-532

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