Conference Information

CAIP 2019: International Conference on Computer Analysis of Images and Patterns

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Submission Date:
2019-04-01
Notification Date:
Conference Date:
2019-09-02
Location:
Salerno, Italy
Years:
18
CORE: b   QUALIS: b2   Viewed: 29384   Tracked: 12   Attend: 3

Call For Papers

CAIP 2019 (International Conference on Computer Analysis of Images and Patterns) is a CORE B / QUALIS B2 conference held in Salerno, Italy on 2019-09-02. The paper submission deadline is 2019-04-01.

The scope of CAIP 2015 includes, but not limited to, the following areas: 2D-to-3D 3D TV 3D Vision Applications Approximation methods Big data Biometrics Brain-inspired algorithms Calibration techniques Classification Clustering algorithms Color and texture Complex natural images Data models Defocus deblurring Delineation Depth Dimension reduction Document analysis Edge/contour detection Enhancement of video and still images Eye blink detection Face recognition Feature extraction Feature selection Gaussian processes Gaze estimation Gesture recognition Graph-based Methods Grouping Human pose estimation Image and video indexing and database retrieval Image and video processing Image color analysis Image fusion Image representation Image restoration Image-based modeling Information theory Invariance Kernel methods Keypoint detection Logical Combinatorial Pattern Recognition Machine learning Machine vision applications Medical imaging Mixture models Mobile multimedia Model-based vision approaches Morphology Motion Analysis Motion deblurring Multiclassifier system Natural computation for digital imagery Non-photorealistic animation and modeling Novel algorithms and techniques Object modelling Object recognition Particle filter framework Pattern recognition for natural language processing Pattern recognition in audio signals Pattern recognition in financial data Pattern recognition in non-visual data Pattern recognition on mobile devices Performance evaluation Photometric stereo Pose estimation Predictive models Query processing Range image Reconstruction techniques Search problems Segmentation Semantic image labelling Shape recovery from multiple images Shape representation and analysis Smoothing methods Statistical models Stereo image analysis Structural pattern recognition Surveillance Texture Three-dimensional displays Tracking Trainable features Transforms Uncertainty
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