IEEE 10th International Conference on Signal Processing and Machine Learning (SPML 2027)

The IEEE 10th International Conference on Signal Processing and Machine Learning (SPML 2027) presents advances in signal processing and machine learning, covering methods, algorithms, applications, and data-driven intelligence for diverse engineering and computational problems.

Key Topics

• Signal processing theory and methods
  • Analog and Mixed Signal Processing
  • Adaptive Filtering & Signal Processing
  • Audio and Electroacoustics
  • Array Signal Processing
  • Bioimaging and Signal Processing
  • Audio/Speech Processing and Coding
  • Biosignal Processing & Understanding
  • Biometrics & Authentification
  • Communication Signal processing
  • Communication and Broadband Networks
  • Digital Signal Processing
  • Design and Implementation of Signal Processing Systems
  • Hardware Implementation for Signal Processing
  • DSP Implementations and Embedded Systems
  • Image and Multidimensional Signal Processing
  • Higher Order Spectral Analysis
  • Machine Learning for Signal Processing
  • Internet Signal Processing
  • Multimedia & Human-computer Interaction
  • Modulation and Channel Coding
  • Multimedia Signal Processing
  • Multimedia Communications
  • Nonlinear Signal Processing
  • Next Generation Mobile Communications
  • Parallel and Distributed Processing
  • Optical Communications
  • Radar Signal Processing
  • PDE for Image Processing
  • RF and Wireless Communications
  • Rapid Prototyping and Tools for DSP Design
  • Signal Processing and Communications Education
  • Sensor Array and Multi-channel Processing
  • Signal Processing for Security
  • Signal Processing for Communications
  • Ad-Hoc and Sensor Networks
  • Signal Processing Theory and Methods
• Machine learning methods/ algorithms
  • Image Processing & Understanding
  • Computer Vision & Virtual Reality
  • Natural Language Processing
  • Image/Video Processing and Coding
  • Learning and adaptive control
  • Machine learning methods
  • Learning for Handwriting Recognition
  • Learning/adaption of recognition and perception
  • Learning in process automation
  • Learning in Image Pre-Processing and Segmentation
  • Learning of action patterns
  • Learning of appropriate behaviour
  • Feature extractions
  • Learning robots
  • Least-squares SVM (LS-SVM)
  • Support vector machines (SVM)
  • Extreme learning machine (ELM)
  • Twin SVM (TWSVM)
  • Classification techniques
  • Artificial neural network (ANN)
  • Reinforce learning
  • Kernel design
  • Deep learning
• Artificial intelligence and it applications
  • Smart Tranportation
  • Smart Agriculture
  • Smart Mining
  • Smart City
• Data mining and knowledge discovey
  • Rough Set and Soft Computing
  • Three-way decision models and analysis
  • Mining Images in Computer Vision
  • Granular Computing Theory and its Applications
  • Mining Motion from Sequence
  • Mining Images and Texture
  • Network Analysis and Intrusion Detection
  • Neural Methods