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Engineering

    • Software tools for imaging
    • Image-based modeling and algorithms
    • Illumination and reflectance modeling
    • Motion and tracking algorithms + orientation estimation
    • Biometric authentication
    • Event recognition techniques in image sequences
    • Medical image processing and analysis
    • Image geometry and multi-view geometry
    • Segmentation techniques
    • Geometric modeling and fractals
    • Scene and object modeling
    • Image data structures and databases
    • Image compression, coding, and encryption
    • Image display techniques
    • Digital imaging for film and television
    • Image formation techniques
    • Image generation, acquisition, and processing
    • Image feature extraction
    • Novel document image understanding techniques + OCR
    • Enhancement techniques
    • Novel noise reduction algorithms
    • Mathematical morphology
    • 3D imaging
    • Watermarking methods and protection
    • Wavelet methods
    • Wavelets, data hiding, image copyright and related issues
    • Mosaic, image registration and fusion methods
    • Color and texture
    • AI, machine learning, SVT with applications in imaging science
    • Image restoration
    • Printing technologies
    • Interpolation techniques
    • Shape representation
    • Video analysis
    • Indexing and retrieval of images (image databases)
    • Signal and speech processing
    • Object recognition
    • Multi-resolution vision techniques
    • Face recognition, face detection, and gesture recognition
    • Stereo vision
    • Soft computing methods in image processing and vision
    • Machine learning technologies for vision
    • Performance analysis and evaluation (real-time vision)
    • Camera networks and vision
    • Sensors and early vision
    • Active and robot vision
    • Cognitive and biologically inspired vision
    • Fuzzy and neural techniques in vision
    • Graph theory in image processing and vision
    • Special-purpose machine architectures for vision
    • Dimensionality reduction methods in pattern recognition
    • Classification and clustering techniques
    • Symbolic learning
    • Statistical pattern recognition
    • Invariance in pattern recognition
    • Knowledge-based recognition

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