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Works20 from public data
- Video-based Visible-Infrared Person Re-Identification via Style Disturbance Defense and Dual Interaction31
A Style Augmentation, Attack and Defense network with Graph-based dual interaction (SAADG) to guarantee the semantic consistency against both intra- modal discrepancies and inter-modal gap is proposed.
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- NoisyEQA: Benchmarking Embodied Question Answering Against Noisy Queries12
A NoisyEQA benchmark designed to evaluate an agent's ability to recognize and correct noisy questions and a 'Self-Correct Prompting' prompting mechanism to effectively improve the accuracy of agent answers are introduced.
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- Spatiotemporal attention mechanism-based multistep traffic volume prediction model for highway toll stations5
A spatiotemporal attention mechanism-based multistep traffic volume prediction model (SAMM) is proposed that increase the short-term prediction accuracy of the traffic volume, but also improved the interpretability of the model by analyzing the internal attention score learnt by the model.
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- A novel multi-parameter similarity measure of interval neutrosophic sets for medical diagnosis2
This study proposes a novel multi-parameter similarity measure for IVNSs based on the tangent function that satisfies the axiomatic definition and applies it to medical diagnosis, achieving accurate diagnostic results.
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- A Systematic Cooperation Method for In-Car Navigation Based on Future Time Windows2
The experimental results show that the proposed method can significantly reduce the overall travel time of all vehicles, compared to the benchmark Dijkstra algorithm, and the effectiveness of the method in a signalised road network.
- A Method for Traffic Flow Forecasting in a Large-Scale Road Network Using Multifeatures2
An equation for achieving a comprehensive and accurate prediction that effectively combines traffic data and non-traffic data is proposed and a novel prediction model, called the adaptive deep neural network (ADNN), is developed.
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- NoisyEQA: benchmarking Embodied Question Answering with imperfect queries from non-expert users–
A NoisyEQA benchmark designed to evaluate the ability of the robot to identify and correct noisy questions and a ‘Self-Correction’ prompting mechanism to enhance EQA against noise robustness and a novel evaluation metric to measure both noise detection capability and answer quality are introduced.
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- The Prediction of Traffic Flow Based on Long Short-Term Memory Network for All Weather–
Compared with the KNN algorithm and GBDT algorithm, the model of this paper not only has higher prediction accuracy, but also has better adaptability to predict the peak, and when weather is adverse, the algorithm can predict accurately through extracting the relevance of time in data set effectively.
Publication data from OpenAlex; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-11. 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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