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The Int'l Conference on Deep Learning and Computer Vision (DLCV 2019)

DLCV 2019

Date of beginning

Friday, 13 December 2019

Duration

3 days

Deadline for abstracts

Wednesday, 06 November 2019

City

Bangkok

Country

泰国

Contact

Ms. Rolin

E-Mail

This email address is being protected from spambots. You need JavaScript enabled to view it.

Expected participants

100

Memo

The Int'l Conference on Deep Learning and Computer Vision (DLCV 2019) Conference Date: December 13-15, 2019Conference Venue: Bangkok, ThailandWebsite: http://www.janconf.org/conference/DLCV2019/Online Registration System: http://www.janconf.org/RegistrationSubmission/default.aspx?ConferenceID=1201Email: This email address is being protected from spambots. You need JavaScript enabled to view it. The Int'l Conference on Deep Learning and Computer Vision (DLCV 2019) will be held in Bangkok, Thailand during December 13-15, 2019. DLCV 2019 will be a valuable and important platform for inspiring Int’l and interdisciplinary exchange at the forefront of Deep Learning and Computer Vision. If you wish to serve the conference as an invited speaker, please send email to us with your CV. We'll contact with you asap. Publication and Presentation Publication: Open Access Journal,please contact us for detailed informationIndex: CNKI and Google Scholar Note: If you want to present your research results but do NOT wish to publish a paper, you may simply submit an Abstract to our Registration System. Contact Us Email: This email address is being protected from spambots. You need JavaScript enabled to view it.:+86 150 7134 3477QQ: 3025797047WeChat: 3025797047 Attendance Methods 1. Submit full paper ( Regular Attendance+Paper Publication+Presentation )You are welcome to submit full paper, all the accepted papers will be published by Open access journal.2. Submit abstract ( Regular Attendance+Abstract+Presentation )3. Regular Attendance ( No Submission Required )    Call for Papers 3D Computer Vision 3D from Multiview and Sensors3D from Single ImagesAction Recognition Adaptive SystemsBiomedical image analysis Biometrics, face and gesture Computational photography, photometryComputer Vision TheoryData Mining for the WebDeep Learning TechniquesDeep model-based and data-efficient reinforcement learningEfficient (Bayesian) inference for deep learningGenerative models as regularizationHyper-parameter optimizationImage and Video SynthesisImage/Video ProcessingLarge-scale generative modellingLarge-scale optimizationLearning representations for reinforcement learningLow-level vision and Image Processing Machine VisionModel structure optimizationMotion and Tracking NeurocomputingRecognition: detection, categorization, indexing and matching Robot Vision Segmentation, grouping and shape representation Semi-supervised learningStatistical learningStructured learningTemporal models with long-term dependenciesUnsupervised/generative modeling