Aiming at the k-winners-take-all(kWTA)operation,this paper proposes a gradient-based differential kWTA(GDk WTA)*** obtaining the network,theorems and related proofs are provided to guarantee the exponential convergenc...
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Aiming at the k-winners-take-all(kWTA)operation,this paper proposes a gradient-based differential kWTA(GDk WTA)*** obtaining the network,theorems and related proofs are provided to guarantee the exponential convergence and noise resistance of the proposed GD-kWTA ***,numerical simulations are conducted to substantiate the preferable performance of the proposed network as compared with the traditional ***,the GD-k WTA network,backed with a consensus filter,is utilized as a robust control scheme for modeling the competition behavior in the multi-robot coordination,thereby further demonstrating its effectiveness and feasibility.
Large language models cross-domain named entity recognition task in the face of the scarcity of large language labeled data in a specific domain,due to the entity bias arising from the variation of entity information ...
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Large language models cross-domain named entity recognition task in the face of the scarcity of large language labeled data in a specific domain,due to the entity bias arising from the variation of entity information between different domains,which makes large language models prone to spurious correlations problems when dealing with specific domains and *** order to solve this problem,this paper proposes a cross-domain named entity recognition method based on causal graph structure enhancement,which captures the cross-domain invariant causal structural representations between feature representations of text sequences and annotation sequences by establishing a causal learning and intervention module,so as to improve the utilization of causal structural features by the large languagemodels in the target domains,and thus effectively alleviate the false entity bias triggered by the false relevance problem;meanwhile,through the semantic feature fusion module,the semantic information of the source and target domains is effectively *** results show an improvement of 2.47%and 4.12%in the political and medical domains,respectively,compared with the benchmark model,and an excellent performance in small-sample scenarios,which proves the effectiveness of causal graph structural enhancement in improving the accuracy of cross-domain entity recognition and reducing false correlations.
Vision-centric autonomous driving systems require diverse data for robust training and evaluation, which can be augmented by manipulating object positions and appearances within existing scene captures. While recent a...
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The scale of grain production affects human life and development. With the continuous expansion of cultivated land, the reproductive ability of weeds to mutiply gradually increases, which affects the growth of crops. ...
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High-resolution is a key trend in the development of synthetic aperture radar (SAR), which enables the capture of fine details and accurate representation of backscattering properties. However, traditional high-resolu...
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Multipath signal recognition is crucial to the ability to provide high-precision absolute-position services by the BeiDou Navigation Satellite system(BDS).However,most existing approaches to this issue involve supervi...
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Multipath signal recognition is crucial to the ability to provide high-precision absolute-position services by the BeiDou Navigation Satellite system(BDS).However,most existing approaches to this issue involve supervised machine learning(ML)methods,and it is difficult to move to unsupervised multipath signal recognition because of the limitations in signal *** by an autoencoder with powerful unsupervised feature extraction,we propose a new deep learning(DL)model for BDS signal recognition that places a long short-term memory(LSTM)module in series with a convolutional sparse autoencoder to create a new autoencoder ***,we propose to capture the temporal correlations in long-duration BeiDou satellite time-series signals by using the LSTM module to mine the temporal change patterns in the time ***,we develop a convolutional sparse autoencoder method that learns a compressed representation of the input data,which then enables downscaled and unsupervised feature extraction from long-duration BeiDou satellite series ***,we add an l_(1/2) regularizer to the objective function of our DL model to remove redundant neurons from the neural network while ensuring recognition *** tested our proposed approach on a real urban canyon dataset,and the results demonstrated that our algorithm could achieve better classification performance than two ML-based methods(e.g.,11%better than a support vector machine)and two existing DL-based methods(e.g.,7.26%better than convolutional neural networks).
Counterfeiting is still a pervasive global issue,affecting multiple industries and hindering industrial innovation,while causing substantial financial losses,reputational damage,and risks to consumer *** luxury goods ...
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Counterfeiting is still a pervasive global issue,affecting multiple industries and hindering industrial innovation,while causing substantial financial losses,reputational damage,and risks to consumer *** luxury goods and pharmaceuticals to electronics and automotive parts,counterfeit products infiltrate supply chains,leading to a loss of revenue for legitimate businesses and undermining consumer *** anti-counterfeiting measures,such as holograms,serial numbers,and barcodes,have proven to be insufficient as counterfeiters continuously develop more sophisticated replication *** a result,there is a growing need for more advanced,secure,and reliable methods to prevent *** paper presents a novel,holistic anti-counterfeiting platform that integrates Near Field Communication(NFC)-enabled mobile applications with blockchain technology to provide an innovative,secure,and consumer-friendly authentication *** approach addresses key gaps in existing solutions by incorporating dynamic product identifiers,which make replication significantly more *** system enables consumers to verify the authenticity of products instantly using their smartphones,enhancing transparency and trust in the supply *** technology plays a crucial role in our proposed solution by providing an immutable,decentralized ledger that records product authentication *** ensures that product verification records cannot be tampered with or altered,adding a layer of security that is absent in conventional ***,NFC technology enhances security by offering unique identification capabilities,enabling real-time product *** validate the effectiveness of the proposed system,real-world testing was conducted across different *** results demonstrated the platform’s ability to significantly reduce counterfeit products in the supply chain,offering businesses and consumers a more robust and reliable aut
Given the requirements for robust target classification and accurate target state estimation in visual tracking, SiamFC++ proposes a set of practical guidelines for designing high-performance general-purpose trackers ...
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Accurate classification and segmentation of polyps are two important tasks in the diagnosis and treatment of colorectal cancers. Existing models perform segmentation and classification separately and do not fully make...
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Aiming at the problem that the existing labeled multi-Bernoulli(LMB) method has a single and fixed model set, an LMB maneuvering target tracking algorithm via Takagi-Sugeno-Kang(TSK) iterative regression multiple mode...
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Aiming at the problem that the existing labeled multi-Bernoulli(LMB) method has a single and fixed model set, an LMB maneuvering target tracking algorithm via Takagi-Sugeno-Kang(TSK) iterative regression multiple model is proposed. In the TSK iterative regression modeling, the feature information of the targets is analyzed and represented by multiple semantic fuzzy sets. Then the state is expanded to introduce model information, thereby the adaptive multi-model idea is incorporated into the framework of the LMB method to solve the uncertain maneuverability of moving targets. Finally,the simulation results show that the proposed algorithm can effectively achieve maneuvering target tracking in the nonlinear system.
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