Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Li, Siyi"'
Autor:
Zhang, Mingrui, Wang, Chunyang, Kramer, Stephan, Wallwork, Joseph G., Li, Siyi, Liu, Jiancheng, Chen, Xiang, Piggott, Matthew D.
Solving complex Partial Differential Equations (PDEs) accurately and efficiently is an essential and challenging problem in all scientific and engineering disciplines. Mesh movement methods provide the capability to improve the accuracy of the numeri
Externí odkaz:
http://arxiv.org/abs/2407.00382
This work proposes a novel data-driven model capable of providing accurate predictions for the power generation of all wind turbines in wind farms of arbitrary layout, yaw angle configurations and wind conditions. The proposed model functions by enco
Externí odkaz:
http://arxiv.org/abs/2311.12750
Copper ferrite nanoparticles have catalytic activity for hydrogen peroxide, which can be used in many fields. This characteristic comes from the physical properties of matters at nanometer scale. Thus, controlling the size and aggregation of nanopart
Externí odkaz:
http://arxiv.org/abs/2301.01658
Wind turbine wake modelling is of crucial importance to accurate resource assessment, to layout optimisation, and to the operational control of wind farms. This work proposes a surrogate model for the representation of wind turbine wakes based on a s
Externí odkaz:
http://arxiv.org/abs/2211.13649
MuZero Unplugged presents a promising approach for offline policy learning from logged data. It conducts Monte-Carlo Tree Search (MCTS) with a learned model and leverages Reanalyze algorithm to learn purely from offline data. For good performance, MC
Externí odkaz:
http://arxiv.org/abs/2210.05980
It has been a long history that most object detection methods obtain objects by using the non-maximum suppression (NMS) and its improved versions like Soft-NMS to remove redundant bounding boxes. We challenge those NMS-based methods from three aspect
Externí odkaz:
http://arxiv.org/abs/2112.00342
We introduce Imuge, an image tamper resilient generative scheme for image self-recovery. The traditional manner of concealing image content within the image are inflexible and fragile to diverse digital attack, i.e. image cropping and JPEG compressio
Externí odkaz:
http://arxiv.org/abs/2110.14196
While deep reinforcement learning (RL) methods have achieved unprecedented successes in a range of challenging problems, their applicability has been mainly limited to simulation or game domains due to the high sample complexity of the trial-and-erro
Externí odkaz:
http://arxiv.org/abs/1709.08233
Convolutional neural network (CNN) models have demonstrated great success in various computer vision tasks including image classification and object detection. However, some equally important tasks such as visual tracking remain relatively unexplored
Externí odkaz:
http://arxiv.org/abs/1501.04587