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https://cis.temple.edu/~latecki/Papers/ACM_MM2023.pdf
ABSTRACT Image stitching aims to align a pair of images in the same view. Generating precise alignment with natural structures is challeng-ing for image stitching, as there is no wider field-of-view image as a reference, especially in non-coplanar practical scenarios. In this paper, we propose an unsupervised image stitching frame-work, breaking through the coplanar constraints in homography ...
https://sites.temple.edu/trail/publications/
[DOI] Alkesh Srivastava and Philip Dames. “Speech-Guided Sequential Planning for Autonomous Navigation using Large Language Model Meta AI 3 (Llama3).” International Conference on Social Robotics (ICSR). [arXiv] [DOI] [YouTube] Jun Chen, Mohammed Abugurain, Philip Dames, Shinkyu Park, Fei Xie, and Qi Mao.
https://ronlevygroup.cst.temple.edu/courses/2020_fall/chem5302/lectures/chem5302_lecture2.pdf
Canonical Ensemble: An ensemble with the same Number of molecules, Volume and Temperature, but different Energy per system. (N, V, T)
https://sites.temple.edu/ydong/
About me Research and Publications Achievements Facebook Twitter Google-plus Yuexiao Dong is Associate Professor and Gilliland Research Fellow from the Department of Statistical Science, Fox School of Business, Temple University. Dr. Dong received his Bachelor’s degree in mathematics from Tsinghua University. He obtained his Ph.D. from the Pennsylvania State University in 2009. Dr. Dong’s ...
https://cis.temple.edu/~jiewu/research/publications/Publication_files/Distributed_Deep_Multi-Agent_Reinforcement_Learning_for_Cooperative_Edge_Caching_in_Internet-of-Vehicles.pdf
Abstract—Edge caching is a promising approach to reduce duplicate content transmission in Internet-of-Vehicles (IoVs). Sev-eral Reinforcement Learning (RL) based edge caching methods have been proposed to improve the resource utilization and reduce the backhaul trafic load. However, they only obtain the local sub-optimal solution, as they neglect the influence from environments by other ...
https://scholarshare.temple.edu/bitstream/handle/20.500.12613/4727/LAURETTI_temple_0225E_14256.pdf;sequence=1
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https://cis.temple.edu/~latecki/Papers/skeletonPAMI06.pdf
Skeleton Pruning by Contour Partitioning with Discrete Curve Evolution Xiang Bai, Longin Jan Latecki, Wen-Yu Liu,
https://cis.temple.edu/~wu/research/publications/Publication_files/Joint%20Dynamic%20Grouping%20and%20Gradient%20Coding%20for%20Time-critical%20Distributed%20Machine%20Learning%20in%20Heterogeneous%20Edge%20Networks-FINAL-VERSION.pdf
Abstract—In edge networks, distributed computing resources have been widely utilized to collaboratively perform a machine learning task by multiple nodes. However, the model training time in heterogeneous edge networks is becoming longer because of excessive computation and delay caused by slow nodes, namely stragglers. The parameter server even abandons stragglers which fail to return ...