Dimensionality reduction for AI based hyperspectral image classification based on XAI
研究利用基于AI的降维方法解决木材回收过程中材料回收率低的问题，通过CNN处理高光谱图像，并采用XAI方法提高系统的可解释性。
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Revisiting Multi-Object Tracking Baselines: Hyperparameter Optimization with Multi-Fidelity Greedy Coordinate Search
本文通过应用超参数优化（特别是多保真贪婪坐标搜索方法）来改进多目标跟踪中的手动调参问题，从而提高跟踪性能。
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Change-point analysis: a new perspective for unstable financial markets
本文针对金融市场的不稳定性，提出基于修正Hankel变换和Laplace变换的两类新的非参数变点检测方法，并通过模拟和实际数据验证了其有效性。
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Wiki Dumps to Training Corpora: South Slavic Case
This work proposes a systematic methodology for constructing high-quality training corpora for South Slavic language models from raw Wikimedia data. Starting with multilingual Wiki project texts, the approach first parses Wiki markup to extract natural language content and then employs an n-gram–based redundancy detection mechanism to effectively filter out highly repetitive, low-information articles. This pipeline substantially enhances the linguistic richness and authenticity of the resulting corpus while maintaining cross-lingual applicability. The final resource encompasses seven South Slavic languages, offering a reliable foundation for large language model training and cross-linguistic comparative studies.
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Dimensionality reduction for AI based hyperspectral image classification based on XAI
研究利用基于AI的降维方法解决木材回收过程中材料回收率低的问题，通过CNN处理高光谱图像，并采用XAI方法提高系统的可解释性。
0 citationsRead paper
A Latent Oscillator Measurement Model to Simulate Emotional-Expression Score Dynamics in Video
该研究通过引入潜振荡测量模型(LOMM)来模拟视频中的情感表达分数动态，以解决分类器、视频和记录条件带来的测量误差问题。
0 citationsRead paper
Revisiting Multi-Object Tracking Baselines: Hyperparameter Optimization with Multi-Fidelity Greedy Coordinate Search
本文通过应用超参数优化（特别是多保真贪婪坐标搜索方法）来改进多目标跟踪中的手动调参问题，从而提高跟踪性能。
0 citationsRead paper
Change-point analysis: a new perspective for unstable financial markets
本文针对金融市场的不稳定性，提出基于修正Hankel变换和Laplace变换的两类新的非参数变点检测方法，并通过模拟和实际数据验证了其有效性。
0 citationsRead paper
Wiki Dumps to Training Corpora: South Slavic Case
This work proposes a systematic methodology for constructing high-quality training corpora for South Slavic language models from raw Wikimedia data. Starting with multilingual Wiki project texts, the approach first parses Wiki markup to extract natural language content and then employs an n-gram–based redundancy detection mechanism to effectively filter out highly repetitive, low-information articles. This pipeline substantially enhances the linguistic richness and authenticity of the resulting corpus while maintaining cross-lingual applicability. The final resource encompasses seven South Slavic languages, offering a reliable foundation for large language model training and cross-linguistic comparative studies.
0 citationsRead paper