In this study,a novel Ca2GaTaO6:Sm3+phosphor was developed using the conventional hightemperature solid-phase *** phase structure and morphology test results of phosphor indicate that the Ca2GaTaO6material was success...
详细信息
In this study,a novel Ca2GaTaO6:Sm3+phosphor was developed using the conventional hightemperature solid-phase *** phase structure and morphology test results of phosphor indicate that the Ca2GaTaO6material was successfully synthesized and the Sm3+ions were successfully doped into the host *** utilizing 406 nm excitation,the Ca2GaTaO6:xSm3+phosphor has the strongest emission intensity at 599 nm and shows orange-red emission,which is mainly owing to the4G5/2→6H7/2jump of Sm3+*** the performance of different concentrations of Sm3+ions,3 mol%performs the *** this time,concentration quenching occurs,which is most predominantly induced by dipole-dipole(d-d) *** terms of thermal stability,the Ca2GaTaO6:0.03Sm3+phosphor shows good properties,with the luminescence intensity at 423 K exhibiting 88.17% of that at 298 *** white light-emitting diodes(WLEDs) devices prepared using Ca2GaTaO6:0.03Sm3+phosphor shows warm white light with excellent performance in terms of correlated color temperature and color rendering index(CCT=3642 K,CRI,Ra=93.5).In terms of anticounterfeit inks,the Ca2GaTaO6:0.03Sm3+phosphor also shows good *** research results show that Ca2GaTaO6:Sm3+phosphors have great performance for application in WLEDs and anti-counterfeit inks.
While deep learning techniques have shown promising performance in the Major Depressive Disorder (MDD) detection task, they still face limitations in real-world scenarios. Specifically, given the data scarcity, some e...
详细信息
In light of issues such as unnoticeable texture features and limited resolution of infrared image objects, a lightweight multi-scale feature fusion method for UAV infrared object recognition is presented to enhance th...
详细信息
Autonomous driving technology has made a lot of outstanding achievements with deep learning,and the vehicle detection and classification algorithm has become one of the critical technologies of autonomous driving *** ...
详细信息
Autonomous driving technology has made a lot of outstanding achievements with deep learning,and the vehicle detection and classification algorithm has become one of the critical technologies of autonomous driving *** vehicle instance segmentation can perform instance-level semantic parsing of vehicle information,which is more accurate and reliable than object ***,the existing instance segmentation algorithms still have the problems of poor mask prediction accuracy and low detection ***,this paper proposes an advanced real-time instance segmentation model named FIR-YOLACT,which fuses the ICIoU(Improved Complete Intersection over Union)and Res2Net for the YOLACT ***,the ICIoU function can effectively solve the degradation problem of the original CIoU loss function,and improve the training convergence speed and detection *** Res2Net module fused with the ECA(Efficient Channel Attention)Net is added to the model’s backbone network,which improves the multi-scale detection capability and mask prediction ***,the Cluster NMS(Non-Maximum Suppression)algorithm is introduced in the model’s bounding box regression to enhance the performance of detecting similarly occluded *** experimental results demonstrate the superiority of FIR-YOLACT to the based methods and the effectiveness of all *** processing speed reaches 28 FPS,which meets the demands of real-time vehicle instance segmentation.
Imaging is an important method for astronomy research. In practice, original images acquired by a telescope are often convolved and blurred by the point-spread function(PSF), which is a very unfavorable situation for ...
详细信息
Imaging is an important method for astronomy research. In practice, original images acquired by a telescope are often convolved and blurred by the point-spread function(PSF), which is a very unfavorable situation for many scientific studies including astronomy. This paper introduced a single equation iterative method for solving complex linear equations, and this method can deconvolute dirty images, eliminate the effects of the PSF *** different PSFs, this algorithm shows very good results in deconvolution. Also, with a giant PSF of aperture synthesis imaging, this algorithm improves the peak signal-to-noise ratio and structural similarity of the dirty images by 41.0% and 33.9% on average. In addition, this paper proves that the algorithm can deconvolute the dirty image by making full use of the information of each pixel in the image, even if the dirty image has salt and pepper noise or even lost areas; by its excellent properties of flexible operation to a single pixel, all these bad situations can be dealt with and the image can be restored.
In wireless networks, utilizing sniffers for fault analysis, traffic traceback, and resource optimization is a crucial task. However, existing centralized algorithms cannot be applied to high-density wireless networks...
详细信息
Text-to-image synthesis refers to generating visual-realistic and semantically consistent images from given textual descriptions. Previous approaches generate an initial low-resolution image and then refine it to be h...
详细信息
Text-to-image synthesis refers to generating visual-realistic and semantically consistent images from given textual descriptions. Previous approaches generate an initial low-resolution image and then refine it to be high-resolution. Despite the remarkable progress, these methods are limited in fully utilizing the given texts and could generate text-mismatched images, especially when the text description is complex. We propose a novel finegrained text-image fusion based generative adversarial networks(FF-GAN), which consists of two modules: Finegrained text-image fusion block(FF-Block) and global semantic refinement(GSR). The proposed FF-Block integrates an attention block and several convolution layers to effectively fuse the fine-grained word-context features into the corresponding visual features, in which the text information is fully used to refine the initial image with more details. And the GSR is proposed to improve the global semantic consistency between linguistic and visual features during the refinement process. Extensive experiments on CUB-200 and COCO datasets demonstrate the superiority of FF-GAN over other state-of-the-art approaches in generating images with semantic consistency to the given texts.
Person re-identification is a prevalent technology deployed on intelligent *** have been remarkable achievements in person re-identification methods based on the assumption that all person images have a sufficiently h...
详细信息
Person re-identification is a prevalent technology deployed on intelligent *** have been remarkable achievements in person re-identification methods based on the assumption that all person images have a sufficiently high resolution,yet such models are not applicable to the open *** real world,the changing distance between pedestrians and the camera renders the resolution of pedestrians captured by the camera *** low-resolution(LR)images in the query set are matched with high-resolution(HR)images in the gallery set,it degrades the performance of the pedestrian matching task due to the absent pedestrian critical information in LR *** address the above issues,we present a dualstream coupling network with wavelet transform(DSCWT)for the cross-resolution person re-identification ***,we use the multi-resolution analysis principle of wavelet transform to separately process the low-frequency and high-frequency regions of LR images,which is applied to restore the lost detail information of LR ***,we devise a residual knowledge constrained loss function that transfers knowledge between the two streams of LR images and HR images for accessing pedestrian invariant features at various *** qualitative and quantitative experiments across four benchmark datasets verify the superiority of the proposed approach.
Domain adaptation aims to transfer knowledge from the labeled source domain to an unlabeled target domain that follows a similar but different ***,adversarial-based methods have achieved remarkable success due to the ...
详细信息
Domain adaptation aims to transfer knowledge from the labeled source domain to an unlabeled target domain that follows a similar but different ***,adversarial-based methods have achieved remarkable success due to the excellent performance of domain-invariant feature presentation ***,the adversarial methods learn the transferability at the expense of the discriminability in feature representation,leading to low generalization to the target *** this end,we propose a Multi-view Feature Learning method for the Over-penalty in Adversarial Domain ***,multi-view representation learning is proposed to enrich the discriminative information contained in domain-invariant feature representation,which will counter the over-penalty for discriminability in adversarial ***,the class distribution in the intra-domain is proposed to replace that in the inter-domain to capture more discriminative information in the learning of transferrable *** experiments show that our method can improve the discriminability while maintaining transferability and exceeds the most advanced methods in the domain adaptation benchmark datasets.
Flight data anomaly detection plays an imperative role in the safety and maintenance of unmanned aerial vehicles(UAVs).It has attracted extensive attention from ***,the problems related to the difficulty in obtaining ...
详细信息
Flight data anomaly detection plays an imperative role in the safety and maintenance of unmanned aerial vehicles(UAVs).It has attracted extensive attention from ***,the problems related to the difficulty in obtaining abnormal data,low model accuracy,and high calculation cost have led to severe challenges with respect to its practical ***,in this study,firstly,several UAV flight data simulation softwares are presented based on a brief presentation of the basic concepts of anomalies,the contents of UAV flight data,and the public datasets for flight data anomaly ***,anomaly detection technologies for UAV flight data are comprehensively reviewed,including knowledge-based,model-based,and data-driven ***,UAV flight data anomaly detection applications are briefly described and ***,the future trends and directions of UAV flight data anomaly detection are summarized and prospected,which aims to provide references for the following research.
暂无评论