Parameter Estimation of Ringdown Quasinormal Modes with Autoencoder
本文使用自编码器框架解决引力波信号中准正模式参数估计问题，通过训练潜在空间表示单个模式的物理参数，实现波形降噪和参数估计。
0 citationsRead paper
Selected work
Representative Papers
Enhancing Privacy in Federated Learning via Dual Obfuscation of Gradients and Training Images
本文提出一种双重混淆方法，通过同时混淆梯度信息和训练图像来增强联邦学习中的隐私保护，减少数据恢复攻击的风险。
0 citationsRead paper
Privacy-Preserving Object Detection for Vision Transformer-Based Models
本文提出了一种基于感知加密的隐私保护方法，用于视觉变换器模型的对象检测任务，同时保持高精度。
0 citationsRead paper
Declining Modularity of Intellectual Bases During the Emergence of Research Areas
This study addresses the unclear mechanisms underlying knowledge base restructuring during research field formation by proposing a novel framework that tracks modularity decline in co-citation networks. Establishing this decline as a structural signature of integrative field emergence, the research validates the approach through co-citation network analysis, temporal tracking, and statistical robustness assessments. Empirical results demonstrate that this metric effectively identifies emerging or transitional phases across three distinct domains. By elucidating the evolutionary dynamics of cross-community knowledge integration, this work provides a quantifiable structural basis for formulating research strategies and assessing frontier trends, thereby offering critical insights into the structural reconfiguration of scientific knowledge during periods of disciplinary convergence and transformation.
0 citationsRead paper
Boundary-Continuous Cross-Camera RGB Mapping via Hue-Split Model Trees
This work addresses the problem of RGB color inconsistency across cameras caused by differences in sensor spectral responses and image signal processing pipelines. To tackle this, the authors propose a model tree structure based on recursive hue partitioning, where an affine color correction matrix (CCM) is learned in the logarithmic domain for each node. To mitigate chromatic discontinuities at hue boundaries induced by hard partitioning, they introduce a path-weighted fusion strategy combined with an explicit continuity regularizer defined over boundary prototype pairs and simplex-constrained optimization. Evaluated on the mapping task from Canon EOS-1Ds Mark II to EOS 20D, the method significantly reduces log-RMSE and effectively suppresses false contours near hue thresholds under diverse illumination and exposure conditions, achieving both high colorimetric accuracy and perceptual smoothness.
0 citationsRead paper
Recent publications
Latest Papers
Parameter Estimation of Ringdown Quasinormal Modes with Autoencoder
本文使用自编码器框架解决引力波信号中准正模式参数估计问题，通过训练潜在空间表示单个模式的物理参数，实现波形降噪和参数估计。
0 citationsRead paper
Enhancing Privacy in Federated Learning via Dual Obfuscation of Gradients and Training Images
本文提出一种双重混淆方法，通过同时混淆梯度信息和训练图像来增强联邦学习中的隐私保护，减少数据恢复攻击的风险。
0 citationsRead paper
Privacy-Preserving Object Detection for Vision Transformer-Based Models
本文提出了一种基于感知加密的隐私保护方法，用于视觉变换器模型的对象检测任务，同时保持高精度。
0 citationsRead paper
Declining Modularity of Intellectual Bases During the Emergence of Research Areas
This study addresses the unclear mechanisms underlying knowledge base restructuring during research field formation by proposing a novel framework that tracks modularity decline in co-citation networks. Establishing this decline as a structural signature of integrative field emergence, the research validates the approach through co-citation network analysis, temporal tracking, and statistical robustness assessments. Empirical results demonstrate that this metric effectively identifies emerging or transitional phases across three distinct domains. By elucidating the evolutionary dynamics of cross-community knowledge integration, this work provides a quantifiable structural basis for formulating research strategies and assessing frontier trends, thereby offering critical insights into the structural reconfiguration of scientific knowledge during periods of disciplinary convergence and transformation.
0 citationsRead paper
Boundary-Continuous Cross-Camera RGB Mapping via Hue-Split Model Trees
This work addresses the problem of RGB color inconsistency across cameras caused by differences in sensor spectral responses and image signal processing pipelines. To tackle this, the authors propose a model tree structure based on recursive hue partitioning, where an affine color correction matrix (CCM) is learned in the logarithmic domain for each node. To mitigate chromatic discontinuities at hue boundaries induced by hard partitioning, they introduce a path-weighted fusion strategy combined with an explicit continuity regularizer defined over boundary prototype pairs and simplex-constrained optimization. Evaluated on the mapping task from Canon EOS-1Ds Mark II to EOS 20D, the method significantly reduces log-RMSE and effectively suppresses false contours near hue thresholds under diverse illumination and exposure conditions, achieving both high colorimetric accuracy and perceptual smoothness.
0 citationsRead paper