In the context of rapid technological development today, multi-source and multi-domain data fusion and enhancement techniques have wide applications across various fields. For instance, in intelligent transportation systems, the real-time monitoring and management of traffic conditions can be achieved by fusing data from video surveillance, radar, and onboard sensors. In the military field, the use of infrared, visible light, hyperspectral data, or the fusion of hyperspectral spatial and spectral domains can enhance target detection and recognition capabilities, improving combat effectiveness. Furthermore, in neurorobotics, integrating neural-inspired algorithms and models with multi-source data fusion techniques enables robots to adapt and learn from complex environments, enhancing their cognitive abilities and interaction capabilities. Therefore, multi-source and multi-domain data fusion and enhancement technology have become an important means to enhance the information processing and decision-making capabilities across a wide range of fields, including neurorobotics.
Under this research theme, we encourage researchers to publish experiments and studies on: (i) multi-modal image fusion, including medical images, multi-focus images, infrared and visible images, etc.; (ii) algorithms and applications for image enhancement, including natural images, infrared images, hyperspectral images, etc.; (iii) image-based target detection. Thus, this research theme provides a theoretical basis and technical support for image visual enhancement and target detection.
We look forward to receiving your papers. Research topics may include (but not limited to) the following:
(1) Multi-focus Image Fusion
(2) Medical Image Fusion
(3) Infrared and Visible Image Fusion
(4) Remote Sensing Image Fusion
(5) Underwater Image Enhancement
(6) Infrared Small Target Detection
(7) Hyperspectral Spatial-Spectral Fusion for Camouflage Detection
(8) Bio-inspired approaches for data fusion
In the context of rapid technological development today, multi-source and multi-domain data fusion and enhancement techniques have wide applications across various fields. For instance, in intelligent transportation systems, the real-time monitoring and management of traffic conditions can be achieved by fusing data from video surveillance, radar, and onboard sensors. In the military field, the use of infrared, visible light, hyperspectral data, or the fusion of hyperspectral spatial and spectral domains can enhance target detection and recognition capabilities, improving combat effectiveness. Furthermore, in neurorobotics, integrating neural-inspired algorithms and models with multi-source data fusion techniques enables robots to adapt and learn from complex environments, enhancing their cognitive abilities and interaction capabilities. Therefore, multi-source and multi-domain data fusion and enhancement technology have become an important means to enhance the information processing and decision-making capabilities across a wide range of fields, including neurorobotics.
Under this research theme, we encourage researchers to publish experiments and studies on: (i) multi-modal image fusion, including medical images, multi-focus images, infrared and visible images, etc.; (ii) algorithms and applications for image enhancement, including natural images, infrared images, hyperspectral images, etc.; (iii) image-based target detection. Thus, this research theme provides a theoretical basis and technical support for image visual enhancement and target detection.
We look forward to receiving your papers. Research topics may include (but not limited to) the following:
(1) Multi-focus Image Fusion
(2) Medical Image Fusion
(3) Infrared and Visible Image Fusion
(4) Remote Sensing Image Fusion
(5) Underwater Image Enhancement
(6) Infrared Small Target Detection
(7) Hyperspectral Spatial-Spectral Fusion for Camouflage Detection
(8) Bio-inspired approaches for data fusion