Submission Deadline: 20 December 2024 Submit to Special Issue
Artificial Intelligence (AI) has rapidly advanced in recent years, leading to the emergence of groundbreaking technologies and applications with far-reaching implications. AI has the potential to revolutionize industries, enhance human capabilities, and address complex challenges in innovative ways.
From using convolutional neural networks to extract image features, to advanced natural language processing achieved by Transformer models, and further to employing graph neural networks to analyze complex topological structures, artificial intelligence is driving unprecedented progress. In medical field, AI is facilitating early disease detection and personalized treatment plans, while in finance, it's optimizing risk management and fraud detection. Additionally, autonomous vehicles and smart manufacturing systems are benefiting from AI's ability to process vast amounts of data in real time, enhancing safety and efficiency. With the continued evolution of AI technologies, the potential for their application across diverse domains is immense, promising to reshape the way we live, work, and interact with the world around us.
As AI continues to advance, its impact will be profound, offering transformative solutions to complex problems and paving the way for a more sustainable and inclusive future. This special issue is open to fresh research contributions that introduce novel theories, innovative methodologies, unique application strategies, and investigations of AI across diverse fields. The potential topics encompassed may include, but are not limited to, the following topics:
· Artificial intelligence.
· Multimodal artificial intelligence
· Potential problems, challenges, and applications of large models
· Visual question and answer (VQA), visual reasoning
· Semantic reasoning, semantic representation, knowledge base
· Characterization inference, natural language reasoning
· Machine translation, text sentiment analysis, text classification
· Meta-learning, transfer learning, few-shot learning.
· Contrastive learning, representation learning, reinforcement learning
· Geospatial artificial intelligence, geospatial AI (GeoAI)
· AI in geostatistics, remote sensing, spatio-temporal simulation
· AI for geospatial data acquisition, analysis, planning, and prediction
· Visual augmentation and reconstruction, 3D reconstruction of deformable surfaces
· Visual- and spatial-based perception enhancement and reasoning
Login
Register
Submit a Paper
Propose a Special lssue