This paper proposes a real-time semantics-driven infrared and visible image fusion framework (RSDFusion). A novel semantics-driven image fusion strategy is introduced in image fusion to maximize the retention of significant information of the source image in the fusion image. First, a semantically segmented image of the source image is obtained using a pre-trained semantic segmentation model. Second, masks of significant targets are obtained from the semantically segmented image, and these masks are used to separate the targets in the source and fusion images. Finally, the local semantic loss of the separation target is designed and combined with the overall structural similarity loss of the image to instruct the network to extract appropriate features to reconstruct the fusion image. Experimental results show that the RSDFusion proposed in this paper outperformed other comparative methods on both subjective and objective evaluation of public datasets and that the main target of the source image is better preserved in the fusion image.

For the package or on-chip power distribution network (PDN) design, plane metals are usually adopted. In this paper, we propose a closed-form grid metals solution to calculate the inductance of such grid PDN for the frequencies below its first antiresonant frequency. First, the grid PDN is equivalent to a plane PDN based on the equivalent circuit of their unit cells. Furthermore, the equivalent plane PDN is simplified as an RLCG lumped circuit, where L is the inductance of the grid PDN. Finally, the inductance of the grid PDN is obtained by the mode analysis of the equivalent plane PDN with a modified modal function. The proposed method is scalable, which can calculate the grid PDNs with the size from micrometer to centimeter. To verify the proposed method, a centimeter grid PDN is fabricated. The inductance obtained by the proposed method has a good agreement with that obtained by measurement and 3-D full-wave simulation. The proposed method can also be expanded to the case that the grid PDN has load impedances. In comparison with the numerical methods, the proposed method can give a more easy-to-understand explanation of the new antiresonant frequency produced by the load impedance.