Effects of multiple occupancy and inter-particle interactions on selective transport through narrow channels: theory versus experiment
专题命中 BEV与占用 :occupancy(title,abstract)
Comments 27 pages, 6 figures, 1 Appendix, in press in Biophysical Journal
视觉与机器人
自动驾驶感知、规划、BEV、占用预测、激光雷达和仿真评测。
专题命中 BEV与占用 :occupancy(title,abstract)
Comments 27 pages, 6 figures, 1 Appendix, in press in Biophysical Journal
专题命中 BEV与占用 :occupancy(title,abstract)
Comments 4 pages, 3 figures, accepted in Phys. Rev. B (Phys. Rev. B 78 (2008))
专题命中 BEV与占用 :occupancy(title,abstract)
Comments 5 pages, 7 figures
Journal ref Phys. Rev. B 76, 184435 (2007)
专题命中 BEV与占用 :occupancy(title,abstract)
Comments 6 pages, 2 embedded color figures, to appear in Physical Review B
专题命中 BEV与占用 :occupancy(title,abstract)
Comments 6 pages, 7 figures
Journal ref Phys. Rev. B, 69 235103 (2004)
专题命中 BEV与占用 :occupancy(title,abstract)
Comments 5 pages, 2 figures
专题命中 BEV与占用 :occupancy(title,abstract)
Comments 4 pages, 2 figures
Journal ref Phys.Rev. B70 (2004) 184501
专题命中 BEV与占用 :occupancy(title,abstract)
Comments Published at http://dx.doi.org/10.1214/07-PS092 in the Probability Surveys (http://www.i-journals.org/ps/) by the Institute of Mathematical Statistics (http://www.imstat.org)
Journal ref Probability Surveys 2007, Vol. 4, 146-171
专题命中 BEV与占用 :occupancy(title,abstract)
Journal ref Advances in Applied Probability, 41(2), 600-622 (2009)
专题命中 BEV与占用 :occupancy(title,abstract)
Comments 3 pages, 2 figures, LCWS08 proceedings
专题命中 BEV与占用 :occupancy(title,abstract)
Comments 5 pages, 3 figures
Journal ref Phys. Rev. Lett. 102, 065301 (2009)
专题命中 BEV与占用 :occupancy(title,abstract)
Comments 20 pages
专题命中 BEV与占用 :occupancy(title,abstract)
专题命中 BEV与占用 :occupancy(title,abstract)
Comments 8 pages, 1 figure
专题命中 BEV与占用 :occupancy(title,abstract)
专题命中 BEV与占用 :occupancy(title,abstract)
Comments 9 pages, 4 figure files
Journal ref Phys. Rev. E 72, 031405 (2005)
专题命中 BEV与占用 :occupancy(title,abstract)
Comments Replaced with (approximately) published version
Journal ref Phys. Rev. B 71, 113310 (2005)
专题命中 BEV与占用 :occupancy(title,abstract)
Comments submitted to Journal of Physics A
Journal ref J. Phys. A: Math. Gen. 37, 577-590 (2004)
专题命中 BEV与占用 :occupancy(title,abstract)
Comments Published by the Institute of Mathematical Statistics (http://www.imstat.org) in the Annals of Probability (http://www.imstat.org/aop/) at http://dx.doi.org/10.1214/009117904000000135
Journal ref Annals of Probability 2004, Vol. 32, No. 3B, 2765-2818
专题命中 BEV与占用 :occupancy(title,abstract)
Journal ref Phys. Rev. B, 71, 115315 (2005)
专题命中 BEV与占用 :occupancy(title,abstract)
Comments 4 pages, 2 figures
Journal ref Phys. Rev. B 66, 092402 (2002)
专题命中 BEV与占用 :occupancy(title,abstract)
Comments 9 pages, 4 figures included
Journal ref Phys. Rev. B 63, 085311 (2001)
专题命中 BEV与占用 :occupancy(title,abstract)
Comments 9 pages, Latex, 6 figures
Journal ref Eur. Phys. J. B 5, 317 (1998)
专题命中 BEV与占用 :occupancy(title,abstract)
Comments 19, RevTeX, cond-mat/9305028
HOLO:基于单应图的细粒度视觉定位网络用于标准定义(SD)地图的视觉定位
机构 * Beijing Institute of Technology(北京理工大学) ; University of Science and Technology of China(中国科学技术大学)
专题命中 BEV与占用 :BEV(abstract,abstract_cn);autonomous driving(abstract);分类 cs.CV
AI总结 本文提出了一种基于单应图的视觉定位网络,用于多视角图像与标准定义地图之间的细粒度视觉定位,通过构建满足单应约束的输入对,利用单应关系引导特征融合并限制姿态输出到有效区域,提高了训练效率和定位精度。
掌 sized 全向视觉基于的无人机探索与稀疏拓扑图引导
机构 * Department of Mechanical and Energy Engineering, Southern University of Science and Technology(南方科技大学机械与能源工程系) ; Thrust of Robotics and Autonomous Systems, Hong Kong University of Science and Technology (Guangzhou)(香港科技大学(广州)机器人与自主系统研究所) ; International Digital Economy Academy, Shenzhen, China(深圳国际数字经济学院)
专题命中 BEV与占用 :LiDAR(abstract,abstract_cn);occupancy(abstract);分类 cs.RO
AI总结 本文提出一种轻量级自主探索系统,利用全向视觉和稀疏拓扑图引导,通过多鱼眼相机实现全向视场和深度估计,采用拓扑节点表示前沿区域,减少内存和计算需求,实现在模拟和实际无人机中高效探索。
RAD-2: 在生成器-判别器框架中扩展强化学习
机构 * Huazhong University of Science & Technology(华中科技大学) ; Horizon Robotics
专题命中 BEV与占用 :BEV(abstract,abstract_cn);autonomous driving(abstract);分类 cs.CV
AI总结 RAD-2提出了一种生成器-判别器框架,通过扩散生成器生成轨迹候选并利用RL优化判别器评估长期驾驶质量,从而提升闭环规划的稳定性与安全性,实验显示碰撞率降低56%。
Comments Project page: https://hgao-cv.github.io/RAD-2
SEF-MAP:子空间分解专家融合用于鲁棒多模态高精度地图预测
机构 * National University of Singapore(新加坡国立大学) ; Xiaomi EV(小米电动车) ; Chinese University of Hong Kong(香港中文大学) ; The University of Manchester(曼彻斯特大学) ; Renmin University of China(中国人民大学)
专题命中 BEV与占用 :autonomous driving(abstract);BEV(abstract);LiDAR(abstract);分类 cs.CV
AI总结 SEF-MAP通过子空间分解和专家融合,提升多模态HD地图预测的鲁棒性和准确性。
专题命中 BEV与占用 :autonomous driving(abstract);BEV(abstract);LiDAR(abstract);分类 cs.CV
Comments 13 pages, 9 figures
专题命中 BEV与占用 :autonomous driving(abstract);BEV(abstract);driving perception(abstract);分类 cs.CV
Comments Accepted for publication at the 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 8 pages excluding references, 5 figures