讽刺 发表于 2025-3-26 21:48:47
Depth-NeuS: Neural Implicit Surfaces Learning for Multi-view Reconstruction Based on Depth Information optimization. Additionally, we integrate photometric loss and geometric loss into loss function as geometric consistency loss to achieve geometric constraints. Empirical experiments have showcased the superior performance of Depth-NeuS over existing technologies across various scenarios. MoreoverCoronation 发表于 2025-3-27 03:16:00
http://reply.papertrans.cn/17/1672/167153/167153_32.pngARM 发表于 2025-3-27 06:31:41
Boosting Robustness of Silhouette-Based Gait Recognition Against Adversarial Attacksnhance edge information in images. The objective is to compel deep neural networks to focus more on semantic information in gait silhouette images and reduce feature deviations induced by adversarial perturbations. The method can significantly improve the adversarial robustness of silhouette-based gCostume 发表于 2025-3-27 11:56:53
http://reply.papertrans.cn/17/1672/167153/167153_34.pngThrottle 发表于 2025-3-27 15:16:49
http://reply.papertrans.cn/17/1672/167153/167153_35.pnggene-therapy 发表于 2025-3-27 18:49:44
Sparse Discriminant Graph Embedding for Feature Extractiongonal constraint and a sparse constraint simultaneously, ensuring the preservation of key information from the original data while enhancing robustness against noise. Extensive experiments on four real-world databases demonstrate the competitiveness of SDGE against state-of-the-art feature extractio无能的人 发表于 2025-3-27 22:31:43
A Multi-Scale Additive Enhanced Network for Remote Sensing Scene Classificationting the problem of high inter class similarity. A Multi-Scale Additive Enhanced Network (MSAENet) is proposed based on MSAE Block and Bridging Residual Module (BRM) and is validated on two datasets, WHU-SIRI and AID. Based on experimental data, the classification accuracy of MSAENet is better than人充满活力 发表于 2025-3-28 02:12:54
SeWi: A Framework Enhancing CSI-Based Human Activity Recognitionifferent models as the basic models for SeWi. We also analyze the effective range of hyperparameters for this segmentation method. The results indicate that SeWi exhibits varying degrees of improvement for different models. Of particular note, using ResNet18 as the basic model for SeWi, the accuracyantenna 发表于 2025-3-28 09:55:54
http://reply.papertrans.cn/17/1672/167153/167153_39.png相反放置 发表于 2025-3-28 12:42:51
Research on Hidden Mind-Wandering Detection Algorithm for Online Classroom Based on Temporal Analysiorithm can quickly and effectively detect students’ distraction phenomena, including daydreaming, distraction, and hidden activities like using mobile phones in blind spots of the camera’s visual capture. This research is significant for helping teachers evaluate students’ performance in online clas