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- Highly efficient incremental estimation of Gaussian mixture models for online data stream clustering149
A probability-density-based data stream clustering approach which requires only the newly arrived data, not the entire historical data, to be saved in memory, which is highly efficient in clustering voluminous online data streams when compared to the standard EM algorithm.
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- Heavy metal pollution in vegetables grown in the vicinity of a multi-metal mining area in Gejiu, China: total concentrations, speciation analysis, and health risk116
Investigation of soils and vegetables in a multi-metal mining area, Gejiu, China showed that lead and arsenic were imposing a serious threat on the local residents via vegetable consumption through vegetable consumption.
- Effect of soil washing on heavy metal removal and soil quality: A two-sided coin106
Although soil washing could effectively remove Pb and Cd in soil, it also resulted in a significant decline in soil quality, but soil neutralization could effectively alleviate the negative effects during soil washing.
- PIMNet: A Parallel, Iterative and Mimicking Network for Scene Text Recognition91
A Parallel, Iterative and Mimicking Network (PIMNet) to balance accuracy and efficiency is proposed, which adopts a parallel attention mechanism to predict the text faster and an iterative generation mechanism to make the predictions more accurate.
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- Heavy metal pollution and potential health risks of commercially available Chinese herbal medicines85
The results showed that the Cd, Hg and Cu concentrations in the 60 CHMs exceeded the limiting values of the "Green Trade Standards of Importing & Exporting Medicinal Plants & Preparations" (WM2-2001), with exceedance ratios of 38.8%, 8.3% and 1.7%, respectively, indicating that Cd had relatively low bioactivity and toxicity.
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- NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results45
This paper reviews the challenge on constrained high dynamic range (HDR) imaging that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2022, and the competition set-up, datasets, proposed methods and their results.
- Mask is All You Need41
This work argues that the performance degradation results from the learning confusion issue in the mask head, and proposes instance-aware mask learning in which the Mask R-CNN head learns to predict the shape of the whole instance rather than classify each pixel to text or non-text.
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- Multimodal sentiment analysis based on cross-instance graph neural networks39
A cross-instance graph neural network is proposed that leverages the global characteristics of the dataset to detect sentiments in text-image pairs and a multimodal in-deep fusion with the multihead attention mechanism is implemented to better predict the sentiment of image-text pairs.
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- The order effect in human abductive reasoning: an empirical and computational study36
It is concluded that when little is known about the uncertainty and the dynamics of the environment, the order effect results from one's coherently and dynamically adaptive expectations of the statistical properties of the environments.
- Indole-3-acetic acid promotes cadmium (Cd) accumulation in a Cd hyperaccumulator and a non-hyperaccumulator by different physiological responses33
IAA promotes Cd accumulation in plant shoots by enhancing the accumulation of carotenoids and proline in S. nigrum and maintaining a high leaf SOD activity in S .
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- Graph Convolutional Network Based on Multi-Head Pooling for Short Text Classification31
A Multi-head-Pooling-based Graph Convolutional Network (MP-GCN) for semi-supervised short text classification is proposed, and its three architectures, which focus on the node representation learning of 1-order, 1&2-order of isomorphic graphs, and 1- order of heterogeneous graphs, are introduced.
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- Particle swarm optimization service composition algorithm based on prior knowledge29
According to the analysis of the experimental results, the improved particle swarm service composition method proposed in this paper shows good performance in three aspects: optimality, time complexity and convergence.
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- Multi-Party Empathetic Dialogue Generation: A New Task for Dialog Systems28
A Static-Dynamic model for Multi-Party Empathetic Dialogue Generation,SDMPED, is introduced as a baseline by exploring the static sensibility and dynamic emotion for the multi-party empathetic dialogue learning, the aspects that help SDMPED achieve the state-of-the-art performance.
- A Span-based Multimodal Variational Autoencoder for Semi-supervised Multimodal Named Entity Recognition27
Experimental results demonstrate that the proposed novel span-based multimodal variational autoencoder (SMVAE) model not only outperforms baselines under supervised setting, but also improves MNER performance with less labeled data than existing semi-supervised methods.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-15. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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