Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Francois P. S. Luus"'
Autor:
Sumit Neelam, Srinivas Ravishankar, Young-Suk Lee, Revanth Gangi Reddy, Salim Roukos, Mo Yu, Francois P. S. Luus, G. P. Shrivatsa Bhargav, Achille Fokoue, Dinesh Garg, Udit Sharma, Lucian Popa, Nandana Mihindukulasooriya, Ibrahim Abdelaziz, Alfio Gliozzo, Hima P. Karanam, Alexander G. Gray, Maria Chang, Cristina Cornelio, Dinesh Khandelwal, Tahira Naseem, Naweed Khan, Sairam Gurajada, Pavan Kapanipathi, Yunyao Li, Saswati Dana, Ramón Fernandez Astudillo, Ryan Riegel, Ndivhuwo Makondo, Gaetano Rossiello
Publikováno v:
ACL/IJCNLP (Findings)
Knowledge base question answering (KBQA)is an important task in Natural Language Processing. Existing approaches face significant challenges including complex question understanding, necessity for reasoning, and lack of large end-to-end training data
Publikováno v:
K-CAP
Knowledge capture from human experts in domain-specific settings can benefit from incisive use of machine intelligence to reduce expended time and effort. Such a capability can be of significant value to deep learning, given its demand for large labe
Publikováno v:
ICMLA
Supervised deep learning depends on labeled datasets to define objective categorization of subject matter, but annotation is typically quite expensive for specialized domains. The ISIC 2017 skin lesion and BCCD blood cell image datasets are used to r
Publikováno v:
IEEE Geoscience and Remote Sensing Letters. 12:2448-2452
A multiscale input strategy for multiview deep learning is proposed for supervised multispectral land-use classification, and it is validated on a well-known data set. The hypothesis that simultaneous multiscale views can improve composition-based in
Autor:
Francois P. S. Luus
Publikováno v:
2017 Pattern Recognition Association of South Africa and Robotics and Mechatronics (PRASA-RobMech).
A large corpus of interesting signal events from the Allen Telescope Array (ATA) is investigated to help find signs of extraterrestrial intelligence. The problem of identifying and categorizing different types of radio frequency interference (RFI) in
Publikováno v:
IEEE Geoscience and Remote Sensing Letters. 11:1153-1157
Multitemporal land-use analysis is becoming increasingly important for the effective management of Earth resources. Despite that, consistent differences in the viewing and illumination geometry in satellite-borne imagery introduce some issues in the
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 6:1274-1285
Settlement classifiers for multitemporal satellite image analysis have to overcome numerous difficulties related to across-date variances in viewing- and illumination geometry. Shadow anisotropy is a prominent contributing factor in classifier inaccu
Publikováno v:
SAIEE Africa Research Journal. 101:68-80
A new universal noise-robust lossless compression algorithm based on a decremental redundancy approach with Fountain codes is proposed. The binary entropy code is harnessed to compress complex sources with the addition of a preprocessing system in th
Publikováno v:
IGARSS
Classifier-generic domain adaptation based on feature space matching is applied in this study, with the aim of correcting dataset shifts consisting of both covariate and concept shifts. The feature space transformation between training and test sampl
Publikováno v:
IGARSS
QuickBird imagery acquired on separate dates may have significant differences in viewing- and illumination geometries, which can negatively impact across-date settlement type classification accuracy. The effect of cast shadows on classification accur