7th Symposium on Pattern Recognition and Applications (SPRA 2027)

The 7th Symposium on Pattern Recognition and Applications (SPRA 2027) presents research in pattern recognition across imaging, vision, signal processing and machine learning for scientific, medical and biometric applications.

Key Topics

• Biomedical Image Analysis
  • Molecular and cellular image analysis
  • Medical and biological imaging
  • Segmentation of medical images
  • Volumetric image analysis
  • Medical image and signal analysis
  • Image guidance and robot guidance of interventions
  • Biological image and signal analysis
  • Content-based image retrieval and data mining
  • Deformable object tracking and registration
  • VR/AR in medical education, diagnosis and surgery
  • Computer-aided detection and diagnosis
  • Computational anatomy and digital human
  • Brain–computer interfaces
  • Medical robotics
  • Algorithms for molecular biology
  • Data mining for biological databases
• Computer Vision
  • Early vision
  • Illumination and reflectance modeling
  • 3D shape recovery
  • Image based modeling
  • Biologically motivated vision
  • Motion, tracking and video analysis
  • 2D/3D object detection and recognition
  • Stereo and multiple view geometry
  • Physics-based vision
  • Occlusion and shadow detection
  • Vision for graphics
  • Reconstruction and camera motion estimation
  • Scene understanding
  • Cognitive and embodied vision
  • Vision for robotics
  • Shape modeling and encoding
  • Computational photography
  • Perceptual organization
  • Low-level vision
• Image, Speech, Signal and Video Processing
  • Image and video analysis and understanding
  • Signal, image and video processing
  • Segmentation, features and descriptors
  • Texture and color analysis
  • Spoken language processing
  • Automatic speech and speaker recognition
  • Sensor array and multichannel signal processing
  • Enhancement, restoration and filtering
  • Coding, compression and super-resolution
  • Audio and acoustic processing and analysis
  • Multimedia analysis, indexing and retrieval
• Pattern Recognition and Machine Learning
  • Machine learning and data mining
  • Deep learning
  • Support vector machines and kernel methods
  • Classific