To improve the insufficient generalization and poor cross-domain capability of the existing direct cross-dataset person re-identification methods,a cross-domain person re-identification method combining feature concat...
To improve the insufficient generalization and poor cross-domain capability of the existing direct cross-dataset person re-identification methods,a cross-domain person re-identification method combining feature concatenation and attention(FCANet) is *** deep features of the network are concatenated to complement the feature information and obtain discriminatively feature,and the position attention module is introduced to enhance the data feature representation capability of the cross-domain task,using the joint training network of label smooth cross-entropy loss and triplet loss,model training in the source domain,and directly deploy to the target domain for *** verify the performance of the proposed method,it was experimented on three public datasets of Market1501,DukeMTMC-reID and MSMT17,which mAP and Rank1can reach 51.4%and 62.7% on *** results show that the proposed method has good performance in improving the generalization of cross-domain tasks,and the recognition accuracy outperforms the domain generalization algorithms of comparison.
Conventionally image translation is used to convert synthetic aperture radar (SAR) images to optical ones to increase interpretability. Due to the different imaging natures of SAR range sensing and optical directional...
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Out-of-distribution (OOD) detection aims to identify the test examples that do not belong to the distribution of training data. The distance-based methods, which identify OOD examples based on their distances from the...
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With the development of national economy, people's daily garbage is increasing day by day. Relying on manpower to sort garbage is a heavy workload and low efficiency. In this paper, an automatic garbage classifica...
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Online social networks not only facilitate the dissemination of information, but also increase the risk of rumors. This paper focuses on studying the unidirectional spread of rumors from online social networks to offl...
ISBN:
(纸本)9798400708305
Online social networks not only facilitate the dissemination of information, but also increase the risk of rumors. This paper focuses on studying the unidirectional spread of rumors from online social networks to offline environments. To describe the dynamic process of rumor spreading, we derive a unidirectional coupled network structure and mean-field equations. We illustrate the performance of rumor spreading under various scenarios using computer simulations. The simulations reveal that rumors in unidirectional coupled networks spread faster and wider than those in single layer networks. Furthermore, with the assistance of unidirectional links, rumors tend to persist for a longer duration and cause more severe damages.
Cervical cytologic screening is clinically important for the prevention and diagnosis of cervical cancer. Aiming at the many challenges in the detection of abnormal cervical cells, including the difficult detection of...
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ISBN:
(数字)9798350376548
ISBN:
(纸本)9798350376555
Cervical cytologic screening is clinically important for the prevention and diagnosis of cervical cancer. Aiming at the many challenges in the detection of abnormal cervical cells, including the difficult detection of small targets of abnormal cervical cells, complex backgrounds, and uneven cell morphology, a detection algorithm for abnormal cervical cells based on improved YOLOv7 was proposed. The algorithm utilizes Deformable Convolutional Networks v2 (DCNv2) that adaptively de-tunes the scale and receptive field size to more effectively cope with the complexity and diversity of cervical cell images. The experimental results show that the improved YOLOv7 algorithm mAP achieves 57.26%, up to 73.88% accuracy, and 46.90% recall on the cervical abnormal cell dataset. Compared with the benchmark model, they increased by 4.07%, 3.39%, and 5.69%, respectively.
Based on the demand for ultraviolet detection in environmental monitoring, industrial control, aerospace and other fields, this paper proposes a method based on MoS2@ZnO UV and temperature dual parameter fiber optic s...
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ISBN:
(数字)9798331542283
ISBN:
(纸本)9798331542290
Based on the demand for ultraviolet detection in environmental monitoring, industrial control, aerospace and other fields, this paper proposes a method based on MoS2@ZnO UV and temperature dual parameter fiber optic sensor for composite materials. This sensor is coated with a layer on the surface of the optical fiber MoS2@ZnO. The composite film utilizes the unique physical and chemical properties of Mos2and ZnO to achieve simultaneous monitoring of ultraviolet light and temperature. This sensor has the advantages of simple structure, low cost, and easy integration, providing a new solution for dual parameter monitoring of ultraviolet and temperature.
Density estimation via Gaussian mixture modeling has been successfully applied to image segmentation, speech processing and other fields relevant to clustering analysis and Probability density function (PDF) modeling....
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Density estimation via Gaussian mixture modeling has been successfully applied to image segmentation, speech processing and other fields relevant to clustering analysis and Probability density function (PDF) modeling. Finite Gaussian mixture model is usually used in practice and the selection of number of mixture components is a significant problem in its application. For example, in image segmentation, it is the donation of the number of segmentation regions. The determination of the optimal model order therefore is a problem that achieves widely attention. This paper proposes a degenerating model algorithm that could simultaneously select the optimal number of mixture components and estimate the parameters for Gaussian mixture model. Unlike traditional model order selection method, it does not need to select the optimal number of components from a set of candidate models. Based on the investigation on the property of the elliptically contoured distributions of generalized multivariate analysis, it select the correct model order in a different way that needs less operation times and less sensitive to the initial value of EM. The experimental results show the effectiveness of the algorithm.
We present a theoretical investigation of the influence of molecular alignment and orientation on elliptically polarized high-order harmonic generation (HHG) from CO molecules exposed to a linearly polarized pulse. Th...
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We present a theoretical investigation of the influence of molecular alignment and orientation on elliptically polarized high-order harmonic generation (HHG) from CO molecules exposed to a linearly polarized pulse. The results show that the ellipticity of HHG observed in a partially aligned or oriented CO molecular ensemble significantly deviates from that of the individual response. Additionally, we find that the ellipticity of HHG in the CO molecular ensemble exhibits strong dependence on the degree of molecular alignment/orientation as well as the time delay between the alignment/orientation and probe pulses. More importantly, under the proper alignment/orientation angle, a large HHG ellipticity can be achieved from the partially aligned/oriented molecular ensemble at a moderate degree of alignment/orientation. These findings relax the experimental requirement of a high degree of molecular alignment/orientation for harmonic generation with large ellipticity.
Based on the demand for ultraviolet detection in environmental monitoring, industrial control, aerospace and other fields, this paper proposes a method based on MoS2@ZnO UV and temperature dual parameter fiber optic s...
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