Role of transforming growth factor-βin peripheral nerve regeneration

Injuries caused by trauma and neurodegenerative diseases can damage the peripheral nervous system and cause functional deficits.Unlike in the central nervous system,damaged axons in peripheral nerves can be induced to regenerate in response to intrinsic cues after reprogramming or in a growth-promoting microenvironment created by Schwann cells.However,axon regeneration and repair do not automatically result in the restoration of function,which is the ultimate therapeutic goal but also a major clinical challenge.Transforming growth factor(TGF)is a multifunctional cytokine that regulates various biological processes including tissue repair,embryo development,and cell growth and differentiation.There is accumulating evidence that TGF-βfamily proteins participate in peripheral nerve repair through various factors and signaling pathways by regulating the growth and transformation of Schwann cells;recruiting specific immune cells;controlling the permeability of the blood-nerve barrier,thereby stimulating axon growth;and inhibiting remyelination of regenerated axons.TGF-βhas been applied to the treatment of peripheral nerve injury in animal models.In this context,we review the functions of TGF-βin peripheral nerve regeneration and potential clinical applications.

Transforming growth factor-β1 and vascular endothelial growth factor levels in senile acute myeloid leukemia and correlation with prognosis

BACKGROUND Acute myeloid leukemia(AML)is a disease in which immature hematopoietic cells accumulate in the bone marrow and continuously expand,inhibiting hematopoiesis.The treatment and prognosis of this disease have always been unsatisfactory.AIM To investigate the correlation between vascular endothelial growth factor(VEGF)and transforming growth factor-β1(TGFβ1)expression and prognosis in older adults with AML.METHODS This study enrolled 80 patients with AML(AML group),including 36 with complete response(AML-CR),23 with partial response(AML-PR),and 21 with no response(AML-NR).The expression levels of VEGF and TGFβ1 were detected by reverse transcription polymerase chain reaction in bone marrow mononuclear cells isolated from 56 healthy controls.Kaplan-Meier analysis was performed to assess overall survival(OS)and progression-or disease-free survival(DFS).Prognostic risk factors were analyzed using a Cox proportional hazards model.RESULTS The AML group showed a VEGF level of 2.68±0.16.VEGF expression was lower in patients with AML-CR than those with AML-PR or AML-NR(P<0.05).TGFβ1 expression in the AML group was 0.33±0.05.Patients with AML-CR showed a higher TGFβ1 expression than those with AML-PR or AML-NR(P<0.05).VEGF and TGFβ1 expression in patients with AML was significantly correlated with the counts of leukocytes,platelets,hemoglobin,and peripheral blood immature cells(P<0.05);Kaplan-Meier survival analysis revealed that patients with high TGFβ1 expression had better OS and DFS than those with low TGFβ1 expression(P<0.05),whereas patients with low VEGF levels showed better OS and DFS than those with high VEGF levels(P<0.05).VEGF,TGFβ1,and platelet count were identified by the Cox proportional hazards model as independent risk factors for OS(P<0.05),while VEGF,TGFβ1,and white blood cell count were independent risk factors for DFS(P<0.05).CONCLUSION Decreased VEGF expression and increased TGFβ1 expression in patients with AML provide valuable references for determining and individualizing clinical treatment strategies.

Roles of transforming growth factor-βsignaling in liver disease

In this editorial we expand the discussion on the article by Zhang et al published in the recent issue of the World Journal of Hepatology.We focus on the diagnostic and therapeutic targets identified on the basis of the current understanding of the molecular mechanisms of liver disease.Transforming growth factor-β(TGF-β)belongs to a structurally related cytokine super family.The family members display different time-and tissue-specific expression patterns associated with autoimmunity,inflammation,fibrosis,and tumorigenesis;and,they participate in the pathogenesis of many diseases.TGF-βand its related signaling pathways have been shown to participate in the progression of liver diseases,such as injury,inflammation,fibrosis,cirrhosis,and cancer.The often studied TGF-β/Smad signaling pathway has been shown to promote or inhibit liver fibrosis under different circumstances.Similarly,the early immature TGF-βmolecule functions as a tumor suppressor,inducing apoptosis;but,its interaction with the mitogenic molecule epidermal growth factor alters this effect,activating anti-apoptotic signals that promote liver cancer development.Overall,TGF-βsignaling displays contradictory effects in different liver disease stages.Therefore,the use of TGF-βand related signaling pathway molecules for diagnosis and treatment of liver diseases remains a challenge and needs further study.In this editorial,we aim to review the evidence for the use of TGF-βsignaling pathway molecules as diagnostic or therapeutic targets for different liver disease stages.

Transforming growth factor-beta 1 enhances discharge activity of cortical neurons

Transforming growth factor-beta 1(TGF-β1)has been extensively studied for its pleiotropic effects on central nervous system diseases.The neuroprotective or neurotoxic effects of TGF-β1 in specific brain areas may depend on the pathological process and cell types involved.Voltage-gated sodium channels(VGSCs)are essential ion channels for the generation of action potentials in neurons,and are involved in various neuroexcitation-related diseases.However,the effects of TGF-β1 on the functional properties of VGSCs and firing properties in cortical neurons remain unclear.In this study,we investigated the effects of TGF-β1 on VGSC function and firing properties in primary cortical neurons from mice.We found that TGF-β1 increased VGSC current density in a dose-and time-dependent manner,which was attributable to the upregulation of Nav1.3 expression.Increased VGSC current density and Nav1.3 expression were significantly abolished by preincubation with inhibitors of mitogen-activated protein kinase kinase(PD98059),p38 mitogen-activated protein kinase(SB203580),and Jun NH2-terminal kinase 1/2 inhibitor(SP600125).Interestingly,TGF-β1 significantly increased the firing threshold of action potentials but did not change their firing rate in cortical neurons.These findings suggest that TGF-β1 can increase Nav1.3 expression through activation of the ERK1/2-JNK-MAPK pathway,which leads to a decrease in the firing threshold of action potentials in cortical neurons under pathological conditions.Thus,this contributes to the occurrence and progression of neuroexcitatory-related diseases of the central nervous system.

A study on the treatment of chloasma with moxibustion based on the theory of“Yang transforming Qi,and Yin shaping”

Background:“Yang Transforming Qi and Yin shaping”comes from“Plain Question Yin and Yang should be like the theory”.Chinese medicine believes that the imbalance of yin and yang is the cause of human diseases.One of the strengths of TCM in treating diseases is holistic regulation.The theory of“Yang transforming Qi,and Yin shaping”implies a strong holistic view.Chloasma,one of the common skin diseases,seriously affects the physical and mental health of patients due to its unclear etiology,difficult treatment and easy recurrence.The occurrence and development of chloasma are closely related to internal organs.This paper is based on the theory of internal meridian,“Yang transforming Qi,and Yin shaping”which attaches importance to the concept of“Yang Qi”,from a new understanding of the pathogenesis etiology of chloasma.Methods:The author believes that the incidence of the disease is the deficiency of Yang Qi,which can’t promote the movement of Qi and blood to nourish the face,resulting in tangible material condensation,so proposes that this disease needs to be promoted by Yang transforming Qi and warm to dissipate.Moxibustion belongs to the fire,and its warming effect can dissipate the tangible evil.Results:Combined with clinical practice and the theory of internal meridian,the author elaborated that moxibustion is one of the effective methods for treating chloasma,which provides a new way of thinking for the treatment of chloasma.Conclusion:“Yang Transforming Qi and Yin shaping”can be used to guide the treatment of chloasma.

Plasma Levels of Transforming Growth Factor-Beta 1 in Women with Pelvic Organ Prolapse

Objective: In women with pelvic organ prolapse (POP), decreased expression of transforming growth factor-beta 1 (TGF-β1) has been shown in POP tissues. However, no studies have evaluated plasma TGF-β1 levels in patients with POP, so it is unknown whether they are also changed or not. Therefore, we compared plasma TGF-β1 levels in women with and without POP. Methods: Participants were 49 women with POP and 23 healthy control women. All participants were postmenopausal. We measured plasma TGF-β1 and compared data between patients with POP and controls, and between patients with uterine prolapse (UP, n = 19) and those with a cystocele (CC, n = 30). In addition, in patients, we assessed the POP quantification system (POP-Q) stage. Results: Plasma TGF-β1 levels were significantly lower in patients than in healthy controls. POP-Q stage was not significantly different between the UP and CC subgroups, but POP-Q stage IV was diagnosed in 63% of patients with UP and 7% of those with CC. Plasma TGF-β1 levels were significantly lower in the CC subgroup than in the UP subgroup. Conclusion: Plasma TGF-β1 is decreased in POP. It remains unclear whether the lower levels indicate a reduction in systemic TGF-β1 activity, but they can be assumed to reflect reduced TGF-β1 expression in POP tissues.

Effect of T-regulatory cells and interleukin-35, interleukin-10, and transforming growth factor-beta on diffuse large B-cell lymphoma

BACKGROUND Diffuse large B-cell lymphoma(DLBCL)is an aggressive non-Hodgkin lymphoma that affects B lymphocytes.It can develop in the lymph nodes and can be localized or generalized.Despite DLBCL being considered potentially curable,little research has been conducted on the relationship between the body's immune response and DLBCL.AIM To study the expression and significance of T-regulatory cells(Tregs)interleukin(IL)-35,IL-10,and transforming growth factor-beta(TGF-β)in DLBCL.METHODS Data from 82 patients with DLBCL who were initially admitted to The First Affiliated Hospital of Ningbo University(Zhejiang Province,China)between January 2017 and June 2022 and treated with standard first-line regimens were reviewed.Three patients were lost to follow-up;thus,79 patients were included in the statistical analysis and then divided into three groups according to the evaluation of clinical efficacy:Incipient(new-onset and treatment-naïve),effectively treated,and relapsed-refractory.Thirty healthy individuals were included in the control group.The expression of peripheral blood T lymphocytes and their associated factors IL-35,IL-10,and TGF-βin the four groups were observed.RESULTS In contrast to the successfully treated and normal control groups,both the incipient and relapse-refractory groups exhibited greater proportions of CD4-positive(+)Tregs(P<0.05),whereas the proportion of CD8+Tregs did not differ substantially between the groups.Serum levels of IL-35 and IL-10 in the incipient and relapsed-refractory groups were higher than those in the effectively treated and normal control groups(P<0.05).There was no statistically significant distinction in the expression level of TGF-βbetween the groups(P>0.05).The correlation between IL-35 and IL-10 concentrations was significantly positive,with a correlation coefficient of 0.531(P<0.05).The correlation between IL-35 and TGF-βconcentration was significantly positive,with a correlation coefficient of 0.375(P<0.05).The correlation between IL-10 and TGF-βconcentration was significantly positive,with a correlation coefficient of 0.185(P<0.05).The expression concentrations of IL-35,IL-10 and TGF-βwere apparently and positively correlated(P<0.05).CONCLUSION Tregs IL-35,and IL-10 may be closely associated with the occurrence and development of DLBCL and the detection of related indices may be helpful in the analysis of disease prognosis.

基于RoBERTa和图增强Transformer的序列推荐方法

自推荐系统出现以来,有限的数据信息就一直制约着推荐算法的进一步发展。为降低数据稀疏性的影响,增强非评分数据的利用率,基于神经网络的文本推荐模型相继被提出,但主流的卷积或循环神经网络在文本语义理解和长距离关系捕捉方面存在明显劣势。为了更好地挖掘用户与商品之间的深层潜在特征,进一步提高推荐质量,提出一种基于Ro BERTa和图增强Transformer的序列推荐(RGT)模型。引入评论文本数据,首先利用预训练的Ro BERTa模型捕获评论文本中的字词语义特征,初步建模用户的个性化兴趣,然后根据用户与商品的历史交互信息,构建具有时序特性的商品关联图注意力机制网络模型,通过图增强Transformer的方法将图模型学习到的各个商品的特征表示以序列的形式输入Transformer编码层,最后将得到的输出向量与之前捕获的语义表征以及计算得到的商品关联图的全图表征输入全连接层,以捕获用户全局的兴趣偏好,实现用户对商品的预测评分。在3组真实亚马逊公开数据集上的实验结果表明,与Deep FM、Conv MF等经典文本推荐模型相比,RGT模型在均方根误差(RMSE)和平均绝对误差(MAE)2种指标上有显著提升,相较于最优对比模型最高分别提升4.7%和5.3%。

基于Depth-wise卷积和视觉Transformer的图像分类模型

图像分类作为一种常见的视觉识别任务,有着广阔的应用场景。在处理图像分类问题时,传统的方法通常使用卷积神经网络,然而,卷积网络的感受野有限,难以建模图像的全局关系表示,导致分类精度低,难以处理复杂多样的图像数据。为了对全局关系进行建模,一些研究者将Transformer应用于图像分类任务,但为了满足Transformer的序列化和并行化要求,需要将图像分割成大小相等、互不重叠的图像块,破坏了相邻图像数据块之间的局部信息。此外,由于Transformer具有较少的先验知识,模型往往需要在大规模数据集上进行预训练,因此计算复杂度较高。为了同时建模图像相邻块之间的局部信息并充分利用图像的全局信息,提出了一种基于Depth-wise卷积的视觉Transformer(Efficient Pyramid Vision Transformer,EPVT)模型。EPVT模型可以实现以较低的计算成本提取相邻图像块之间的局部和全局信息。EPVT模型主要包含3个关键组件:局部感知模块(Local Perceptron Module,LPM)、空间信息融合模块(Spatial Information Fusion,SIF)和“+卷积前馈神经网络(Convolution Feed-forward Network,CFFN)。LPM模块用于捕获图像的局部相关性;SIF模块用于融合相邻图像块之间的局部信息,并利用不同图像块之间的远距离依赖关系,提升模型的特征表达能力,使模型学习到输出特征在不同维度下的语义信息;CFFN模块用于编码位置信息和重塑张量。在图像分类数据集ImageNet-1K上,所提模型优于现有的同等规模的视觉Transformer分类模型,取得了82.6%的分类准确度,证明了该模型在大规模数据集上具有竞争力。

CNN-Transformer特征融合多目标跟踪算法

在卷积神经网络(CNN)中,卷积运算能高效地提取目标的局部特征,却难以捕获全局表示;而在视觉Transformer中,注意力机制可以捕获长距离的特征依赖,但会忽略局部特征细节。针对以上问题,提出一种基于CNN-Transformer双分支主干网络进行特征提取和融合的多目标跟踪算法CTMOT(CNN-transformer multi-object tracking)。使用基于CNN和Transformer双分支并行的主干网络分别提取图像的局部和全局特征。使用双向桥接模块(two-way braidge module,TBM)对两种特征进行充分融合。将融合后的特征输入两组并行的解码器进行处理。将解码器输出的检测框和跟踪框进行匹配,完成多目标跟踪任务。在多目标跟踪数据集MOT17、MOT20、KITTI以及UADETRAC上进行评估,CTMOT算法的MOTP和IDs指标在四个数据集上均达到了SOTA效果,MOTA指标分别达到了76.4%、66.3%、92.36%和88.57%,在MOT数据集上与SOTA方法效果相当,在KITTI数据集上达到SOTA效果。由于同时完成目标检测和关联,能够端到端进行目标跟踪,跟踪速度可达35 FPS,表明CTMOT算法在跟踪的实时性和准确性上达到了较好的平衡,具有较大潜力。

基于Transformer和自适应特征融合的矿井低照度图像亮度提升和细节增强方法

高质量矿井影像为矿山安全生产提供保障,也有利于提高后续图像分析技术的性能。矿井影像受低照度环境的影响,易出现亮度低,照度不均,颜色失真,细节信息丢失严重等问题。针对上述问题,提出一种基于Transformer和自适应特征融合的矿井低照度图像亮度提升和细节增强方法。基于生成对抗思想搭建生成对抗式主体模型框架,使用目标图像域而非单一参考图像驱动判别器监督生成器的训练,实现对低照度图像的充分增强;基于特征表示学习理论搭建特征编码器,将图像解耦为亮度分量和反射分量,避免图像增强过程中亮度与颜色特征相互影响从而导致颜色失真问题;设计CEM-Transformer Encoder通过捕获全局上下文关系和提取局部区域特征,能够充分提升整体图像亮度并消除局部区域照度不均;在反射分量增强过程中,使用结合CEM-Cross-Transformer Encoder的跳跃连接将低级特征与深层网络处特征进行自适应融合,能够有效避免细节特征丢失,并在编码网络中添加ECA-Net,提高浅层网络的特征提取效率。制作矿井低照度图像数据集为矿井低照度图像增强任务提供数据资源。试验显示,在矿井低照度图像数据集和公共数据集中,与5种先进的低照度图像增强算法相比,该算法增强图像的质量指标PSNR、SSIM、VIF平均提高了16.564%,10.998%,16.226%和14.438%,10.888%,14.948%,证明该算法能够有效提升整体图像亮度,消除照度不均,避免颜色失真和细节丢失,实现矿井低照度图像增强。

融合卷积注意力和Transformer架构的行人重识别方法

行人重识别技术是智能安防系统中的重要方法之一,为构建一个适用各种复杂场景的行人重识别模型,基于现有的卷积神经网络和Transformer模型,提出一种融合卷积注意力和Transformer(FCAT)架构的方法,以增强Transformer对局部细节信息的关注。所提方法主要将卷积空间注意力和通道注意力嵌入Transformer架构中,分别加强对图像中重要区域的关注和对重要通道特征的关注,以进一步提高Transformer架构对局部细节特征的提取能力。在3个公开行人重识别数据集上的对比消融实验证明,所提方法在非遮挡数据集上取得了与现有方法相当的结果,在遮挡数据集上的性能得到显著提升。所提方法更加轻量化,在不增加额外计算量和模型参数的情况下,推理速度得到了提升。

基于残差U-Net和自注意力Transformer编码器的磁场预测方法

利用有限元方法对几何结构复杂的电机和变压器进行磁场分析,存在仿真时间长且无法复用的问题。因此,该文提出一种基于残差U-Net和自注意力Transformer编码器的磁场预测方法。首先建立永磁同步电机(PMSM)和非晶合金变压器(AMT)有限元模型,得到深度学习训练所需的数据集;然后将Transformer模块与U-Net模型结合,并引入短残差机制建立ResUnet-Transformer模型,通过预测图像的像素实现磁场预测;最后通过Targeted Dropout算法和动态学习率调整策略对模型进行优化,解决拟合问题并提高预测精度。计算实例证明,ResUnet-Transformer模型在PMSM和AMT数据集上测试集的平均绝对百分比误差(MAPE)均小于1%,且仅需500组样本。该文提出的磁场预测方法能减少实际工况和多工况下精细模拟和拓扑优化的时间和资源消耗,亦是虚拟传感器乃至数字孪生的关键实现方法之一。

基于Transformer和动态3D卷积的多源遥感图像分类

多源遥感数据具有互补性和协同性,近年来,基于深度学习的方法已经在多源遥感图像分类中取得了一定进展,但当前方法仍面临关键难题,如多源遥感图像特征表达不一致,融合困难,基于静态推理范式的神经网络缺乏对不同类别地物的适应性。为解决上述问题,提出了基于跨模态Transformer和多尺度动态3D卷积的多源遥感图像分类模型。为提高多源特征表达的一致性,设计了基于Transformer的融合模块,借助其强大的注意力建模能力挖掘高光谱和LiDAR数据特征之间的相互作用;为提高特征提取方法对不同地物类别的适应性,设计了多尺度动态3D卷积模块,将输入特征的多尺度信息融入卷积核的调制,提高卷积操作对不同地物的适应性。采用多源遥感数据集Houston和Trento对所提方法进行验证,实验结果表明:所提方法在Houston和Trento数据集上总体准确率分别达到94.60%和98.21%,相比MGA-MFN等主流方法,总体准确率分别至少提升0.97%和0.25%,验证了所提方法可有效提升多源遥感图像分类的准确率。

考虑特征重组与改进Transformer的风电功率短期日前预测方法

短期日前风电功率预测对电力系统调度计划制定有重要意义,该文为提高风电功率预测的准确性,提出了一种基于Transformer的预测模型Powerformer。模型通过因果注意力机制挖掘序列的时序依赖;通过去平稳化模块优化因果注意力以提高数据本身的可预测性;通过设计趋势增强和周期增强模块提高模型的预测能力;通过改进解码器的多头注意力层,使模型提取周期特征和趋势特征。该文首先对风电数据进行预处理,采用完全自适应噪声集合经验模态分解(complete ensemble empirical mode decomposition with adaptive noise,CEEMDAN)将风电数据序列分解为不同频率的本征模态函数并计算其样本熵,使得风电功率序列重组为周期序列和趋势序列,然后将序列输入到Powerformer模型,实现对风电功率短期日前准确预测。结果表明,虽然训练时间长于已有预测模型,但Poweformer模型预测精度得到提升;同时,消融实验结果验证了模型各模块的必要性和有效性,具有一定的应用价值。

基于Transformer的陶瓷轴承表面缺陷检测方法

针对传统机器视觉检测方法中,由于陶瓷轴承滚动体表面曲率大、对比度低,表面成像模糊导致后续缺陷检测精度低的问题,提出一种基于Transformer的超分辨率残差网络。首先,网络使用残差学习策略,通过预测模糊图像与清晰图像之间的差值,实现超分辨率任务;其次,在网络上前端插入通道注意力模块和空间注意力模块并改进L2多头自注意力模块,以增强图像纹理、改善梯度爆炸问题;最后,针对超分辨率重建任务,提出一种两阶段训练策略优化训练过程。自建陶瓷轴承表面缺陷数据集上的大量实验结果表明,所提出网络模型在客观指标与主观评价上均优于MSESRGAN、VSDR等超分辨率算法,重建图像SSIM为0.939,PSNR为36.51 dB。

基于遥感多参数和CNN-Transformer的冬小麦单产估测

为了提高冬小麦单产估测精度,改善估产模型存在的高产低估和低产高估等现象,以陕西省关中平原为研究区域,选取旬尺度条件植被温度指数(VTCI)、叶面积指数(LAI)和光合有效辐射吸收比率(FPAR)为遥感特征参数,结合卷积神经网络(CNN)局部特征提取能力和基于自注意力机制的Transformer网络的全局信息提取能力,构建CNN-Transformer深度学习模型,用于估测关中平原冬小麦产量。与Transformer模型(R^(2)为0.64,RMSE为465.40 kg/hm^(2),MAPE为8.04%)相比,CNN-Transformer模型具有更高的冬小麦单产估测精度(R^(2)为0.70,RMSE为420.39 kg/hm^(2),MAPE为7.65%),能够从遥感多参数中提取更多与产量相关的信息,且对于Transformer模型存在的高产低估和低产高估现象均有所改善。基于5折交叉验证法和留一法进一步验证了CNN-Transformer模型的鲁棒性和泛化能力。此外,基于CNN-Transformer模型捕获冬小麦生长过程的累积效应,分析逐步累积旬尺度输入参数对产量估测的影响,评估模型对于冬小麦不同生长阶段的累积过程的表征能力。结果表明,模型能有效捕捉冬小麦生长的关键时期,3月下旬至5月上旬是冬小麦生长的关键时期。

ConvFormer:基于Transformer的视觉主干网络

针对主流Transformer网络仅对输入像素块做自注意力计算而忽略了不同像素块间的信息交互,以及输入尺度单一导致局部特征细节模糊的问题,本文提出一种基于Transformer并用于处理视觉任务的主干网络ConvFormer. ConvFormer通过所设计的多尺度混洗自注意力模块(Channel-Shuffle and Multi-Scale attention,CSMS)和动态相对位置编码模块(Dynamic Relative Position Coding,DRPC)来聚合多尺度像素块间的语义信息,并在前馈网络中引入深度卷积提高网络的局部建模能力.在公开数据集ImageNet-1K,COCO 2017和ADE20K上分别进行图像分类、目标检测和语义分割实验,ConvFormer-Tiny与不同视觉任务中同量级最优网络RetNetY-4G,Swin-Tiny和ResNet50对比,精度分别提高0.3%,1.4%和0.5%.

基于Transformer的多尺度遥感语义分割网络

为了提升遥感图像语义分割效果,本文针对分割目标类间方差小、类内方差大的特点,从全局上下文信息和多尺度语义特征2个关键点提出一种基于Transformer的多尺度遥感语义分割网络(muliti-scale Transformer network,MSTNet)。其由编码器和解码器2个部分组成,编码器包含基于Transformer改进的视觉注意网络(visual attention network,VAN)主干和基于空洞空间金字塔池化(atrous spatial pyramid pooling, ASPP)结构改进的多尺度语义特征提取模块(multi-scale semantic feature extraction module, MSFEM)。解码器采用轻量级多层感知器(multi-layer perception,MLP)配合编码器设计,充分分析所提取的包含全局上下文信息和多尺度表示的语义特征。MSTNet在2个高分辨率遥感语义分割数据集ISPRS Potsdam和LoveDA上进行验证,平均交并比(mIoU)分别达到79.50%和54.12%,平均F1-score(m F1)分别达到87.46%和69.34%,实验结果验证了本文所提方法有效提升了遥感图像语义分割的效果。

引入轻量级Transformer的无人机视觉跟踪

随着无人机在军事和民用领域的广泛运用,对于高精度、低功耗智能无人机跟踪系统的需求日益增加。针对目标跟踪算法在无人机跟踪场景下很难平衡跟踪精度和跟踪速度的问题,提出一种引入轻量级Transformer的孪生网络无人机目标跟踪算法SiamLT。使用Transformer对AlexNet网络进行改进,在增加最小计算量的情况下捕获全局特征信息。在目标模板与搜索区域匹配方面,联合Transformer和深度互相关运算提出一种二元相关模块,同时捕获目标模板与搜索区域之间的局部相关性和全局依赖关系。在分类回归网络中引入距离交并比,并采用多监督策略训练网络,以获取更准确的目标位置。在UAV123和UAV20L跟踪基准上的实验结果表明,SiamLT算法优于主流的目标跟踪算法,更有效地平衡了跟踪精度和跟踪速度。