no code implementations • 16 Mar 2024 • Jizhe Dou, Haotian Zhang, Guodong Sun
To address this issue, we present a hybrid-action deep reinforcement learning framework, called HaDMC, which uses a standard policy learning algorithm to generate latent continuous actions.
1 code implementation • 27 Feb 2024 • Guodong Sun, Yuting Peng, Le Cheng, Mengya Xu, An Wang, Bo Wu, Hongliang Ren, Yang Zhang
The precise segmentation of ore images is critical to the successful execution of the beneficiation process.
1 code implementation • 10 Nov 2023 • Guodong Sun, Delong Huang, Yuting Peng, Le Cheng, Bo Wu, Yang Zhang
At the same time, the ore distribution is stacked, and it is difficult to identify the complete features.
1 code implementation • 11 Aug 2023 • Yang Zhang, Chenyun Xiong, Junjie Liu, Xuhui Ye, Guodong Sun
Efficient RGB-D semantic segmentation has received considerable attention in mobile robots, which plays a vital role in analyzing and recognizing environmental information.
Ranked #57 on Semantic Segmentation on NYU Depth v2
no code implementations • 3 Jul 2023 • Yang Zhang, Huilin Pan, Yang Zhou, Mingying Li, Guodong Sun
Efficient visual fault detection of freight trains is a critical part of ensuring the safe operation of railways under the restricted hardware environment.
1 code implementation • 2 May 2023 • Yang Zhang, Le Cheng, Yuting Peng, Chengming Xu, Yanwei Fu, Bo Wu, Guodong Sun
For the ore particle size detection, obtaining a sizable amount of high-quality ore labeled data is time-consuming and expensive.
no code implementations • 26 Nov 2022 • Yang Zhang, Yang Zhou, Huilin Pan, Bo Wu, Guodong Sun
Fault detection for key components in the braking system of freight trains is critical for ensuring railway transportation safety.
no code implementations • 1 Aug 2022 • Bin Shi, Guodong Sun
In this paper, we propose a sampling algorithm based on state-of-the-art statistical machine learning techniques to obtain conditional nonlinear optimal perturbations (CNOPs), which is different from traditional (deterministic) optimization methods. 1 Specifically, the traditional approach is unavailable in practice, which requires numerically computing the gradient (first-order information) such that the computation cost is expensive, since it needs a large number of times to run numerical models.
no code implementations • 25 May 2022 • Guodong Sun, Yang Zhou, Huilin Pan, Bo Wu, Ye Hu, Yang Zhang
In this paper, we propose a lightweight NMS-free framework to achieve real-time detection and high accuracy simultaneously.
no code implementations • 5 Jan 2022 • Yang Zhang, Yang Yang, Chenyun Xiong, Guodong Sun, Yanwen Guo
Encoder-decoder models have been widely used in RGBD semantic segmentation, and most of them are designed via a two-stream network.
Ranked #13 on Semantic Segmentation on SUN-RGBD (using extra training data)
1 code implementation • 22 Oct 2021 • Yang Zhang, Moyun Liu, Huiming Zhang, Guodong Sun, Jingwu He
To reduce time complexity while improving performance, a sparse representation of global nodes based on noise-free online low-rank representation is used to obtain a global graph at each scale.
no code implementations • 17 Jan 2021 • Zejin Wang, Guodong Sun, Lina Zhang, Guoqing Li, Hua Han
The TSA interpolation module aggregates temporal contexts and then adaptively samples the spatial-related features with the proposed residual spatial adaptive block.