Scene Classification Combining Low-level and Semantic Modeling Strategies

Scene classification is an important issue in the field of computer vision. AltHough considerable progress has been made, it remains a challenging issue. Most of the current scene classification approaChes are based on either low-level or semantic modeLing strategies. This paper presents a novel scene classification approach based on combining low-level and semantic modeLing strategies. The experimental results show that the proposed approach performs competitively against previous methods across three pubLicly and commonly used data sets.