Qiya Su

Complete genome sequence analysis of Pestalotiopsis microspora, a fungal pathogen causing kiwifruit postharvest rots

Lei Deng, Xufang Qiu, Qiya Su, Hui Pan et autres

BACKGROUND: The postharvest rot of kiwifruit is one of the most devastating diseases affecting kiwifruit quality worldwide. However, the genomic basis and pathogenicity mechanisms of kiwifruit rot pathogens are lacking. Here we report the first whole genome sequence of Pestalotiopsis microspora, one …

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DDFNet-A: Attention-Based Dual-Branch Feature Decomposition Fusion Network for Infrared and Visible Image Fusion

Qiancheng Wei, Ying Liu, Ben Zhang, Qiya Su et autres

The fusion of infrared and visible images aims to leverage the strengths of both modalities, thereby generating fused images with enhanced visible perception and discrimination capabilities. However, current image fusion methods frequently treat common features between modalities (modality-commonality) and unique features from …

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LASDNet: A Lightweight Adaptive Surface Defect Detection Network

Qiancheng Wei, Yi Yuan, Ying Liu, Mohammed Ali Mohammed Al-Hababi et autres

Surface defect detection is an important task in industry. However, surface defect detection still faces many challenges, including variations in aspect ratios, similarity with the background, and difficulty in detecting small defects. In this paper, we propose LASDNet, a novel model for …

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Small Object Detection on the Water Surface Based on Radar and Camera Fusion

Qiancheng Wei, Xiaoping Jiang, Ying Liu, Qiya Su et autres

With the growing applications of water operations, water surface object detection tasks are facing new challenges. In this paper, we focus on improving the performance of water surface small object detection. Due to the limitations of single-sensor in water environments, we propose …

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Electroencephalography recognition based on encephalic region and temporal sequence transformer

Mingyang Sun, Qiya Su, Qing Yu Zhao, Chao Liu

Abstract Stereoscopic vision is the key to good motor control and accurate cognition, and its formation is closely related to brain control. The early methods of measuring stereoscopic vision rely on the subject’s judgment, which might be influenced by inadvertent misjudgments. To …

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A CrossNet-Based Prototype Network with Similarity Guidance for Few-Shot Radar Target Detection

Huiling Xu, Zhengguo Shang, Qiya Su, Xinzhi Li et autres

Few-shot radar object Detection poses a challenging task of recognizing the radar target from with only few numbers of annotated example as supervision. In this article, we propose Cross-SGNet, a Prototype Network based on CrossNet to tackle the few-shot radar target detection …

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Adaptive Threshold Hierarchical Incremental Learning Method

Xingyu Li, Shengbo Dong, Qiya Su, Muyao Yu et autres

Traditional deep convolutional neural networks have achieved excellent performance on various machine learning tasks. Still, they perform poorly in continuous data stream environments, where models trained on new datasets often suffer from a significant drop in performance on old datasets, a phenomenon …

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Observability Analysis and Navigation Algorithm for Distributed Satellites System Using Relative Range Measurements

Qiya Su, Yi Huang

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Quasi-consistent fusion navigation algorithm for DSS

Qiya Su, Yi Huang, Yanguang Jiang, Haitao Fang

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Quasi-consistency extended Kalman filter based fusion navigation algorithm for distributed satellites system

Qiya Su, Yanguang Jiang, Yi Huang, Haitao Fang

The navigation problem of the distributed satellites system (DSS) employing relative range measurements and some inertial position measurements of partial satellites is investigated. A fusion navigation algorithm based on the quasi-consistency extended Kalman filter (QCEKF) is proposed, which can provide an on-line …

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Autonomous observability of multisatellite systems using relative range measurements

Qiya Su, Yi Huang

The problem of autonomous orbit determination of the formation flying missions based solely on relative range measurements without any external signals is studied. Observability for all of the participating satellites in this problem is analyzed based on the nonlinear Keplerian model with …

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Accuracy Evaluation of Least-Squares Method for a Class of Systems with Multi-Errors in Input and Output**This work is supported by the National Key Basic Research Program of China (973 Program) under Grant No. 2014CB845301 and the National Center for Mathematics and Interdisciplinary Sciences, Chinese Academy of Sciences

Wenyan Bai, Qiya Su, Wenchao Xue, Yi Huang

This paper aims to evaluate the identification error of Least Square (LS) method for a class of systems with bias error, scale error and random noise in the measurement of both control input and output. According to the relation between the LS …

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