Monocular 6D pose estimation is a functional task in the field of computer vision and robotics. In recent years, 2D-3D correspondence-based methods have achieved improved performance multiview depth data-based scenes. However, for monocular estimation, these are affected by prediction results correspondences robustness perspective-n-point (PnP) algorithm. There still difference distance from ex...

In recent years, transformers have shown great potential in hyperspectral image processing and also been gradually applied target detection (HTD). Nonetheless, applying a typical transformer to HTD remains challenging. The heavy computation burden of the multi-head self-attention (MSA) limits its efficient HTD, while limited ability extract local spectral features can reduce discrimination lear...

Abstract The power transformer is one of the important pieces equipment in grid system, and its normal operation related to safety reliability whole system. There are many factors influencing vibration operation, characteristics complex, so it difficult be directly used for state analysis. This paper proposes a method signal analysis based on continuous wavelet time-frequency graph. segmented s...

Micro-expressions are the small, brief facial expression changes that humans momentarily show during emotional experiences, and their data annotation is complicated, which leads to scarcity of micro-expression data. To extract salient distinguishing features from a limited dataset, we propose an attention-based multi-scale, multi-modal, multi-branch flow network thoroughly learn motion informat...

The distribution network reconfiguration problem (DNRP) refers to the challenge of searching for a given power configuration with better operating conditions, such as minimized energy losses and improved voltage levels. To accomplish that, this paper revisits branch exchange heuristics presents method in which it is coupled other techniques evolutionary metaheuristics cluster analysis. methodol...

As demands for understanding visual style among interior scenes increase, estimating compatibility is becoming challenging. In particular, furniture styles are difficult to define due their various elements, such as color and shape. a result, an ambiguous concept. To reduce ambiguity, Siamese networks have frequently been used estimate by adding features that represent the style. However, it st...

Polarimetric synthetic aperture radar (PolSAR) images contain useful information, which can lead to extensive land cover interpretation and a variety of output products. In contrast optical imagery, there are several challenges in extracting beneficial features from PolSAR data. Deep learning (DL) methods provide solutions address feature extraction challenges. The convolutional neural networks...

This paper deals with MIP-based primal heuristics to be used within a branch-and-cut approach for solving multi-layer telecommunication network design problems. Based on a mixed-integer programming formulation for two network layers, we present three heuristics for solving important subproblems, two of which solve a sub-MIP. On multi-layer planning instances with many parallel logical links, we...

The Drosophila tracheal system, a tubular network, is formed from isolated ectodermal metameres by guided branch outgrowth and branch fusion. Branch outgrowth is triggered by the localized and transient activity of Branchless (Bnl/dFGF). Here, we report the discovery of a mesodermal cell that links the leading cells of outgrowing main branches 2.5 hr before they fuse. This bridge-cell serves as...

Observing that Semantic features learned in an image classification task and Appearance features learned in a similarity matching task complement each other, we build a twofold Siamese network, named SA-Siam, for real-time object tracking. SA-Siam is composed of a semantic branch and an appearance branch. Each branch is a similaritylearning Siamese network. An important design choice in SA-Siam...