HIUFE: Hybrid intelligence-based unauthorized farmland excavation scene cognition

作者：Shunxi Yin, Wanzeng Liu, Jun Chen, Jiaxin Ren, Yuan Tao, Yilin Wang, Jiadong Zhang · 发表于：ISPRS Journal of Photogrammetry and Remote Sensing · 年份：2025 · DOI：10.1016/j.isprsjprs.2025.06.016 · 被引用次数：5 · 研究领域：Image Processing and 3D Reconstruction、3D Surveying and Cultural Heritage、Landslides and related hazards

Unauthorized farmland excavation refers to activities such as digging, mining, and related resource development within farmland boundaries, conducted without legal authorization or in violation of relevant regulations. These activities directly contribute to the destruction and functional degradation of farmland, posing significant threats to national food security and social stability. Existing farmland monitoring methods utilizing video recognition exhibit limitations, including high false positive rates, and low levels of automation. To address these challenges, this paper proposes a hybrid intelligence-based cognitive approach to video scene analysis for unauthorized farmland excavation activities. At the data level, a video dataset capturing the behavioral interactions of construction machinery in unauthorized farmland excavation scenes is constructed, incorporating temporal and spatial dimensions to comprehensively depict interaction features among the machinery. At the algorithmic level, considering the frequent motion of objects and the high timeliness requirements in video scenes, expert knowledge is integrated to enhance YOLOv8, specifically proposing a hybrid intelligence-based object behavior recognition model that accurately captures subtle feature differences in the same object under different behaviors. During the inference phase, a knowledge graph and reasoning mechanism are constructed to deeply integrate dynamic video information with domain knowledge, overc...