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RGB-T semantic segmentation is a key technique for autonomous driving scenes understanding. For the existing RGB-T semantic segmentation methods, however, the effective exploration of the complementary relationship between different modalities is not implemented in the information interaction between multiple levels. To address such an issue, the Context-Aware Interaction Network (CAINet) is proposed for RGB-T semantic segmentation, which constructs interaction space to exploit auxiliary tasks and global context for explicitly guided learning. Specifically, we propose a Context-Aware Complementary Reasoning (CACR) module aimed at establishing the complementary relationship between multimodal features with the long-term context in both spatial and channel dimensions. Further, considering the importance of global contextual and detailed information, we propose the Global Context Modeling (GCM) module and Detail Aggregation (DA) module, and we introduce specific auxiliary supervision to explicitly guide the context interaction and refine the segmentation map. Extensive experiments on two benchmark datasets of MFNet and PST900 demonstrate that the proposed CAINet achieves state-of-the-art performance. The code is available at https://github.com/YingLv1106/CAINet., Comment: 13 pages, 7 figures, Accepted by IEEE Transactions on Multimedia 2024

In this paper, we study the existence of normalized solutions to the following Kirchhoff equation with a perturbation: $$ \left\{ \begin{aligned} &-\left(a+b\int _{\mathbb{R}^{N}}\left | \nabla u \right|^{2} dx\right)\Delta u+\lambda u=|u|^{p-2} u+h(x)\left |u\right |^{q-2}u, \quad \text{ in } \mathbb{R}^{N}, \\ &\int_{\mathbb{R}^{N}}\left|u\right|^{2}dx=c, \quad u \in H^{1}(\mathbb{R}^{N}), \end{aligned} \right. $$ where $1\le N\le 3, a,b,c>0, 1\leq q<2$, $\lambda \in \mathbb{R}$. We treat three cases. (i)When $2

In this paper, we study the following fractional Schr\"{o}dinger equation with prescribed mass \begin{equation*} \left\{ \begin{aligned} &(-\Delta)^{s}u=\lambda u+a(x)|u|^{p-2}u,\quad\text{in $\mathbb{R}^{N}$},\\ &\int_{\mathbb{R}^{N}}|u|^{2}dx=c^{2},\quad u\in H^{s}(\mathbb{R}^{N}), \end{aligned} \right. \end{equation*} where $02s$, $2+\frac{4s}{N}0$, $\lambda\in \mathbb{R}$ and $a(x)\in C^{1}(\mathbb{R}^{N},\mathbb{R}^{+})$ is a potential function. By using a minimax principle, we prove the existence of bounded state normalized solution under various conditions on $a(x)$.

In this paper, we study a class of fractional Schr\"{o}dinger equation \begin{equation} \label{eq0} \left\{ \begin{aligned} &(-\Delta)^{s}u=\lambda u+a(x)|u|^{p-2}u,\\ &\int_{\mathbb{R}^{N}}|u|^{2}dx=c^{2},\ u\in H^{s}(\mathbb{R}^{N}), \end{aligned} \right. \end{equation} where $N>2s$, $s\in(0,1)$ and $p\in(2,2+4s/N), c>0$. $a(x)\in C(\mathbb{R}^{N},\mathbb{R})$ is a positive potential function. By using Fixed Point Theorem of Brouwer, barycenter function and variational method, we obtain the existence of normalized bound solutions for the problem.

In this paper, based on an optimization problem, a sketch-and-project method for solving the linear matrix equation AXB = C is proposed. We provide a thorough convergence analysis for the new method and derive a lower bound on the convergence rate and some convergence conditions including the case that the coefficient matrix is rank deficient. By varying three parameters in the new method and convergence theorems, the new method recovers an array of well-known algorithms and their convergence results. Meanwhile, with the use of Gaussian sampling, we can obtain the Gaussian global randomized Kaczmarz (GaussGRK) method which shows some advantages in solving the matrix equation AXB = C. Finally, numerical experiments are given to illustrate the effectiveness of recovered methods., Comment: arXiv admin note: text overlap with arXiv:1506.03296, arXiv:1612.06013, arXiv:2204.13920 by other authors

In this paper, we construct a class of nonlinear greedy average block Kaczmarz methods to solve nonlinear problems without computing the Moore-Penrose pseudoinverse. This kind of methods adopts the average technique of Gaussian Kaczmarz method and combines with the greedy strategy, which greatly reduces the amount of computation. The convergence analysis and numerical experiments of the proposed method are given. The numerical results show the effectiveness of the proposed methods.

This paper is devoted to the study of minimal immersions of flat $n$-tori into spheres, especially those immersed by the first eigenfunctions (such immersion is called $\lambda_1$-minimal immersion), which also play important roles in spectral geometry. It is known that there are only two non-congruent $\lambda_1$-minimal $2$-tori in spheres, which are both flat. For higher dimensional case, the Clifford $n$-torus in $\mathbb{S}^{2n-1}$ might be the only known example in the literature. In this paper, by discussing the general construction of homogeneous minimal flat $n$-tori in spheres, we construct many new examples of $\lambda_1$-minimal flat $3$-tori and $4$-tori. In contrast to the rigidity in the case of $2$-tori, we show that there exists a $2$-parameter family of non-congruent $\lambda_1$-minimal flat $4$-tori. It turns out that the examples we constructed exhaust all $\lambda_1$-minimal immersions of conformally flat $3$-tori and $4$-tori in spheres. The classification involves some detailed investigations of shortest vectors in lattices, which can also be used to solve the Berger's problem on flat $3$-tori and $4$-tori. The dilation-invariant functional $\lambda_1(g)V(g)^{\frac{2}{n}}$ about the first eignvalue is proved to have maximal value among all flat $3$-tori and $4$-tori., Comment: 37 pages. A new section about the Berger's probelm on flat 3-tori and 4-tori is added in this version