Academic Journal

Infusion-Net: Inter- and Intra-Weighted Cross-Fusion Network for Multispectral Object Detection

التفاصيل البيبلوغرافية
العنوان: Infusion-Net: Inter- and Intra-Weighted Cross-Fusion Network for Multispectral Object Detection
المؤلفون: Jun-Seok Yun, Seon-Hoo Park, Seok Bong Yoo
المصدر: Mathematics, Vol 10, Iss 21, p 3966 (2022)
بيانات النشر: MDPI AG, 2022.
سنة النشر: 2022
المجموعة: LCC:Mathematics
مصطلحات موضوعية: multispectral object detection, inter- and intra-weighted fusion, high-frequency component, discrete cosine transform, Mathematics, QA1-939
الوصف: Object recognition is conducted using red, green, and blue (RGB) images in object recognition studies. However, RGB images in low-light environments or environments where other objects occlude the target objects cause poor object recognition performance. In contrast, infrared (IR) images provide acceptable object recognition performance in these environments because they detect IR waves rather than visible illumination. In this paper, we propose an inter- and intra-weighted cross-fusion network (Infusion-Net), which improves object recognition performance by combining the strengths of the RGB-IR image pairs. Infusion-Net connects dual object detection models using a high-frequency (HF) assistant (HFA) to combine the advantages of RGB-IR images. To extract HF components, the HFA transforms input images into a discrete cosine transform domain. The extracted HF components are weighted via pretrained inter- and intra-weights for feature-domain cross-fusion. The inter-weighted fused features are transmitted to each other’s networks to complement the limitations of each modality. The intra-weighted features are also used to enhance any insufficient HF components of the target objects. Thus, the experimental results present the superiority of the proposed network and present improved performance of the multispectral object recognition task.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2227-7390
Relation: https://www.mdpi.com/2227-7390/10/21/3966; https://doaj.org/toc/2227-7390
DOI: 10.3390/math10213966
URL الوصول: https://doaj.org/article/3cfb3aeea88141f8a8f6a5afe5654ecc
رقم الانضمام: edsdoj.3cfb3aeea88141f8a8f6a5afe5654ecc
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:22277390
DOI:10.3390/math10213966