Special Session Ⅰ: Application Research of AI in Engineering, Agriculture and Biology

Session Chair: Prof. Wei Zhan——Yangtze University, China


Currently, the application and empowerment of AI in different fields are gaining significant attention.But applying the latest AI technology in professional fields still presents challenges, including difficulties in obtaining high-quality data, dealing with high granularity data, and facing challenges in model transfer ability. Improving algorithms and models to enable AI to assist in managing or solving critical problems in specific professional fields can drive the upgrade and transformation of traditional disciplines.

This special session focuses on research that applies AI to address specific real-world problems across multiple disciplines. We welcome the incorporation of the wide interdisciplinary nature of AI in the articles, including novel research methods, data processing and analysis, AI models, comparisons with existing techniques, improvements, and discussions.

Below is an incomplete list of potential topics to be covered in the Special Session:

  • AI methods and expert systems

  • Applications of AI in engineering

  • Applications of AI in Earth exploration and information technology

  • Applications of AI in bio-informatics

  • Applications of AI in biochemical research methods

  • Smart cities

  • Intelligent transportation systems

Special Session Ⅱ: Signal Processing for Future Smart Radars/Communications

Session Chair: Prof. Xiaolong Chen——Naval Aeronautical University, China

Prof. Xianpeng Wang——Hainan University, China


Signal processing plays a crucial role in the development of future smart radar and communication systems. Envisioned as versatile platforms offering control, computing, communications, localization, and sensing capabilities, these systems incorporate innovative technologies such as massive multiple-input multiple-output (MIMO) antenna arrays, reconfigurable intelligent surfaces, beamforming, and integrated air-ground-space networks to deliver intelligent services. Consequently, signal processing techniques are evolving to meet the complex demands of smart radar and communication systems, including ultra-wideband radio frequency, high-speed ADC/DAC, non-orthogonal waveforms, non-orthogonal multiple access (NOMA), and complex mutual coupling.

This session aims to explore emerging trends, challenges, models, solutions, and applications in signal processing tailored for smart radar and communications. We invite authors to submit original papers presenting novel theoretical and/or application-oriented research encompassing models, algorithms, and practical implementations.

The topics to be covered include, but are not limited to:

  • Blind source separation for smart radar and communications

  • Detection and estimation techniques for smart radar and communications

  • Design and implementation of spatial-temporal-frequency-polarization filters

  • Multi-dimensional direction finding and beamforming in non-ideal scenarios

  • Array signal processing incorporating reconfigurable intelligent surfaces

  • Application of machine learning in array signal processing for smart radar and communications

  • Pre- and post-processing methods for smart radar and communications

  • Analysis techniques for biomedical signals

  • Baseband signal processing techniques for communication signal transmission and reception

  • Signal processing techniques for data hiding and audio watermarking

Special Session Ⅲ: Cognitive Learning and Large-sized Model for Wireless Communication and Intelligent Spectrum Management

Session Chair: Prof. Fuhui Zhou——Nanjing University of Aeronautics and Astronautics, China

Assoc. Prof. Wei Wu——Nanjing University of Posts and Telecommunications, China


Cognitive learning and large-sized models are revolutionizing techniques in the field of wireless communication and intelligent spectrum management, playing a crucial role in shaping the future of communication systems. In the field of wireless communication, research focuses on intelligent antenna design, beamforming, cognitive radio, semantic communication, and integrated air-land-sea networks. In terms of intelligent spectrum management, the main areas of research include dynamic spectrum access, spectrum situation prediction, spectrum sensing and sharing, spectrum map construction, and transmission. Furthermore, evolving cognitive learning technologies such as deep learning, reinforcement learning, knowledge graphs, and the integration of large-sized models enable more efficient, intelligent, and adaptive communication and spectrum management. By intelligently learning and optimizing spectrum behaviors to improve communication efficiency and spectrum resource utilization, it can support the complex and changing communication needs of the future.


The main objective of this special session is to explore emerging trends, challenges, models, solutions, and applications in cognitive learning and large-sized model for wireless communication and intelligent spectrum management. We welcome original papers that present pioneering theoretical and/or application-oriented research, covering a wide range of topics including innovative models, algorithms, and practical implementations.


The topics to be covered include, but are not limited to:

  • Large-scale models for intelligent spectrum management techniques

  • Spectrum situational prediction algorithm and technology research

  • High-precision electromagnetic spectrum map generation and completion

  • Knowledge graph construction and application in intelligent spectrum management

  • Intelligent spectrum allocation and dynamic spectrum access strategy

  • Spectrum sharing mechanism research in cognitive radio systems

  • Cognitive learning-based spectrum data transmission algorithm design

  • Intelligent antenna design and adaptive beamforming

  • Semantic communication based on large language model

Special Session ⅣAgriFuturity-Smart Agriculture Through Artificial Intelligence

Session Chair: Prof. Yi An——Agro-Environmental Protection Institute, Ministry of Agriculture and Rural Affairs, China


Artificial Intelligence (AI) is revolutionizing various industries, and agriculture is no exception. Smart agriculture, also known as precision agriculture, harnesses AI and other cutting-edge technologies to optimize farming practices, improve efficiency, and promote sustainability. By integrating various digital tools, sensors, and data analytics, smart agriculture enables farmers to make more informed decisions and manage their operations more effectively. The integration of AI and smart agriculture technologies holds tremendous potential to address the challenges facing modern agriculture, such as climate change, resource scarcity, and food security. By leveraging data-driven insights and innovative solutions, smart agriculture paves the way for a more sustainable and resilient farming future.

This session aims to explore emerging trends, challenges, models, solutions, and applications in smart agriculture. We invite renowned experts and scholars from domestic and foreign fields of smart agriculture to submit original papers presenting novel theoretical and application oriented research encompassing models, algorithms, and practical implementations. Attendees can not only listen to exciting reports, but also personally participate in face-to-face exchanges and discussions with experts to promote communication, discussion, and cooperation among researchers in this field.

The topics to be covered include, but are not limited to:

  • Agricultural Internet of Things system

  • Agricultural big data analysis and application

  • Intelligent processing and decision-making of agricultural information

  • Intelligent detection and control system for agricultural machinery and equipment

  • Crop growth simulation model

  • Agricultural aviation technology and application

  • Agricultural robots and other technologies

  • Application of sensors in the management of crop seasons

  • Digital Agriculture and Agriculture Information

Special Session Ⅴ: Application of Artificial Intelligence in Geoscience

Session Chair: Prof. Xingong Tang——Yangtze University, China


Artificial intelligence has enormous application potential in the field of geology, such as intelligent equipment, intelligent geological mapping, mineralization prediction, and intelligent monitoring and early warning of geological disasters. In the field of earth science, how to achieve effective monitoring, prediction, and early warning, maintain sustainable development of human society, and achieve harmonious coexistence between humans and nature will be a very challenging issue.  Artificial intelligence will provide new solutions in data storage, data processing, data mining, analysis and prediction, and provide Earth scientists with new ways to solve problems.

This session aims to explore emerging trends, challenges, models, solutions, and applications of AI in Geoscience. We invite authors to submit original papers presenting novel theoretical and/or application-oriented research encompassing models, algorithms, and practical implementations.

Below is an incomplete list of potential topics to be covered in the Special Session:

Topics of interest include but are not limited to:

  • Analysis and Processing of Geoscience Big Data

  • Intelligent processing of Geophysical Data

  • Geophysical intelligent inversion and imaging

  • Geological disaster monitoring and prediction based on artificial intelligence technology and geoscience big data

  • Climate change monitoring based on artificial intelligence models

  • Forest biodiversity monitoring and resource management using deep learning-based models

  • Monitoring and prevention of ecological and environmental disasters based on Remote sensing spatiotemporal big data

  • Geological structure modeling using artificial intelligence technology

  • Semantic recognition in remote sensing and geoscience big data using artificial intelligence technology

Special Session Ⅵ: Frontier Applications of Artificial Intelligence in Remote Sensing

Session Chair: Prof. Wenjiang Huang——Chinese Academy of Sciences, China
Prof. Jingfeng Huang——Zhejiang University, China

Prof. Jingcheng Zhang——Hangzhou Dianzi University, China


With the rapid accumulation of high-resolution remote sensing data and internet geographic information, the demand for intelligent processing and analysis of remote sensing big data is increasing day by day. Artificial intelligence (AI) technology provides strong support for improving the efficiency and accuracy of remote sensing data acquisition, and brings new possibilities for the processing, analysis, and application of remote sensing data. From image recognition to land cover classification, from change detection to environmental monitoring, AI demonstrates extensive and far-reaching applications in the field of remote sensing.

This session aims to explore the latest advances, challenges, and application prospects of AI in the field of remote sensing. We invite authors to submit original papers covering new theories, methods, and applications of AI technology in remote sensing data processing, remote sensing image analysis, and remote sensing applications.

The topics to be covered include, but are not limited to:

  • Remote sensing monitoring of major crop pests and diseases based on artificial intelligence technology

  • Application of deep learning in spatio-temporal big data for forest monitoring

  • Deep learning for crop classification with remote sensing data

  • Application of artificial intelligence and remote sensing in frontier research on agricultural meteorological disasters 

  • Environmental remote sensing monitoring with artificial intelligence technology

  • Application of artificial intelligence in change detection and monitoring

Special Session Ⅶ: Visual Perception, Analysis and Multimodal Generation

Session Chair: Prof. Yuliang Liu——Huazhong University of Science and Technology, China


In practical applications, multimodal data is ubiquitous, covering various forms of information such as vision, hearing, touch, and text. This topic focuses on how to effectively integrate and process information from different modalities in intelligent systems, achieving precise perception, deep understanding, and innovative expression of the complex real world. The research in this field is of great significance for promoting innovation in many fields such as human-computer interaction, intelligent decision-making, information retrieval, education and entertainment.

By hosting this session, we look forward to inspiring more valuable scientific discoveries, accelerating the development of multimodal perception, analysis, and generation technologies, and helping them achieve wider and deeper social applications.

The topics to be covered include, but are not limited to:

  • Object detection and tracking, instance segmentation

  • Text detection

  • Face and action recognition

  • Attribute learning

  • Scene understanding, semantic segmentation, panoptic segmentation, etc.

  • Large language model and vision-language model

  • Image or video synthesis and editing

  • 3D Vision

Special Session Ⅷ: Applications of Artificial Intelligence in Remote Sensing

Session Chair: Prof. Guisong Xia——Wuhan University, China

Prof. Lefei Zhang——Wuhan University, China

Prof. Zhiwei Ye——Hubei University of Technology, China


The advancement and development of society today are greatly facilitated by the crucial roles played by Artificial Intelligence (AI) and remote sensing technology. Remote sensing technology acquires large-scale geospatial data through satellites, drones, and other means, while artificial intelligence, with its powerful data processing and analytical capabilities, enables more efficient and precise applications of remote sensing data in fields such as resource management, environmental monitoring, and urban planning compared to traditional methods. The rise of AI has provided novel solutions for remote sensing data processing. The integration of AI and remote sensing technology has led to significant breakthroughs in key tasks such as target detection, semantic segmentation, change detection, and image quality enhancement. By utilizing neural networks, it is possible to significantly enhance the accuracy of target detection and recognition in remote sensing images, enhance degraded remote sensing images, and efficiently analyze vast spatial data, providing important and effective research foundations for subsequent advanced tasks, thus enabling rapid development of relevant applications in the field of remote sensing. Therefore, this special issue aims to focus on the latest research progress in the integration of AI technology with remote sensing applications, thereby promoting innovation and development in related fields.

The broad topics include (but are not limited to):

  • Hyperspectral/Multispectral/Optical Remote Sensing Image Quality Enhancement and Restoration with Artificial Intelligence Technology

  • Remote Sensing Image Interpretation with Artificial Intelligence Technology

  • Application of Artificial Intelligence in Satellite Remote Sensing Image Segmentation and Object Recognition

  • Application of Artificial Intelligence in High-Resolution Remote Sensing Images Change Detection

  • Multi-Model Remote Sensing Data Feature Extraction and Fusion

  • Intelligent Processing of UAV Remote Sensing Image Data

Special Session Ⅸ: Artificial Intelligence and Remote Sensing Technologies for Water Security and Environment Management

Session Chair: Prof. Pingping Luo——Chang'an University, China


Artificial intelligence and remote sensing technologies play a key role in water security and water environment management. These technologies are envisioned as dynamic tools that provide comprehensive monitoring, analysis and intervention capabilities, integrating advanced artificial intelligence algorithms and remote sensing data to facilitate proactive decision-making and resource allocation in water-related applications .Leveraging methods such as machine learning, deep learning, and image processing, these techniques can provide real-time insights into water quality, quantity, and distribution across various spatial and temporal scales.

This session aims to explore in depth the latest progress, challenges, methods and applications of water security management and water environment governance based on artificial intelligence and remote sensing technology. We encourage researchers to submit original contributions presenting innovative theoretical frameworks and/or practical implementations addressing the diverse needs of water management and governance.

The topics to be addressed include, but are not limited to:

  • Integration of AI and remote sensing for water quality monitoring and assessment

  • Detection and classification of water-related features using satellite imagery and UAV data

  • Development of predictive models for water availability and demand forecasting

  • Optimization of water distribution networks using AI-driven algorithms

  • Analysis of hydrological parameters using time-series remote sensing data

  • Fusion of multi-source data for comprehensive water resource management

  • Application of AI in early warning systems for natural disasters affecting water resources

  • Implementation of smart sensing technologies for real-time water quality monitoring

  • Assessment of the impact of climate change on water resources using remote sensing and AI methodologies