Výsledky vyhledávání - "Encoder–decoder Structure"

Rethinking Transformers for Semantic Segmentation of Remote Sensing Images Autor Liu, Yuheng, Zhang, Yifan, Wang, Ye, Mei, Shaohui

“…Transformer has been widely applied in image processing tasks as a substitute for convolutional neural networks (CNNs) for feature extraction due to its…”
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Learnable PM diffusion coefficients and reformative coordinate attention network for low dose CT denoising Autor Zhang, Haowen, Zhang, Pengcheng, Cheng, Weiting, Li, Shu, Yan, Rongbiao, Hou, Ruifeng, Gui, Zhiguo, Liu, Yi, Chen, Yang

“…Various deep learning methods have recently been used for low dose CT (LDCT) denoising. Aggressive denoising may destroy the edge and fine anatomical…”
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Ship Segmentation via Encoder-Decoder Network With Global Attention in High-Resolution SAR Images Autor Li, Jichao, Gou, Shuiping, Li, Ruimin, Chen, Jia-Wei, Sun, Xiaolong

“…Ship detection in the synthetic aperture radar (SAR) image is of great significance in the fields of military and coastal defense. Most ship detection methods…”
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A Dual Autoencoder-like NMF with Higher-Order Graph Regularization for Topic Modeling Autor Majidi, Maryam, Saberi-Movahed, Farid, Ghasemzadeh, Mohammad, Vahdati, Sahar

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Fine-grained highway autonomous vehicle lane-changing trajectory prediction based on a heuristic attention-aided encoder-decoder model Autor Wei, Cheng, Hui, Fei, Yang, Zijiang, Jia, Shuo, Khattak, Asad J.

“…•A novel lane-changing trajectory segmentation and sampling algorithm is proposed.•Heuristic attention-aided encoder-decoder network is developed.•Both vehicle…”
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Cascaded transformer U-net for image restoration Autor Yan, Longbin, Zhao, Min, Liu, Shumin, Shi, Shuaikai, Chen, Jie

“…•A cascaded multi-stage framework is designed based on the transformer for image restoration.•The self-attention mechanism and cascaded architecture enable the…”
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Learning Representations for Facial Actions From Unlabeled Videos Autor Li, Yong, Zeng, Jiabei, Shan, Shiguang

“…Facial actions are usually encoded as anatomy-based action units (AUs), the labelling of which demands expertise and thus is time-consuming and expensive. To…”
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Predicting water quality in municipal water management systems using a hybrid deep learning model Autor Luo, Wenxian, Huang, Leijun, Shu, Jiabin, Feng, Hailin, Guo, Wenjie, Xia, Kai, Fang, Kai, Wang, Wei

“…Increasing municipal waste generation puts more and more municipal water resources at high risk. Accurate prediction of water quality becomes critical for…”
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Learning Feature Embedding Refiner for Solving Vehicle Routing Problems Autor Li, Jingwen, Ma, Yining, Cao, Zhiguang, Wu, Yaoxin, Song, Wen, Zhang, Jie, Chee, Yeow Meng

“…While the encoder-decoder structure is widely used in the recent neural construction methods for learning to solve vehicle routing problems (VRPs), they are…”
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Spatio-Temporal Network for Sea Fog Forecasting Autor Park, Jinhyeok, Lee, Young Jae, Jo, Yongwon, Kim, Jaehoon, Han, Jin Hyun, Kim, Kuk Jin, Kim, Young Taeg, Kim, Seoung Bum

“…Sea fog can seriously affect schedules and safety by reducing visibility during marine transportation. Therefore, the forecasting of sea fog is an important…”
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A I-ED-TSP: Association and Integration Encoder–Decoder for Traveling Shortest Path Planning Autor Bin Hu, Renjun Zhang

“…Traveling shortest path planning, encompassing the Traveling Salesman Problem (TSP) in graph theory, holds profound significance. The motivation for addressing…”
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Recurrent Residual Dual Attention Network for Airborne Laser Scanning Point Cloud Semantic Segmentation Autor Zeng, Tao, Luo, Fulin, Guo, Tan, Gong, Xiuwen, Xue, Jingyun, Li, Hanshan

“…Kernel point convolution (KPConv) can effectively represent the point features of point cloud data. However, KPConv-based methods just consider the local…”
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A Dual-Encoder-Single-Decoder Based Low-Dose CT Denoising Network Autor Han, Zefang, Shangguan, Hong, Zhang, Xiong, Zhang, Pengcheng, Cui, Xueying, Ren, Huiying

“…Generative adversarial networks (GAN) have shown great potential for image quality improvement in low-dose CT (LDCT). In general, the shallow features of…”
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A&I-ED-TSP: Association and Integration Encoder-Decoder for Traveling Shortest Path Planning Autor Hu, Bin, Zhang, Renjun

“…Traveling shortest path planning, encompassing the Traveling Salesman Problem (TSP) in graph theory, holds profound significance. The motivation for addressing…”
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Multi-task federated learning with encoder–decoder structure: enabling collaborative learning across different tasks Autor Zhou, Jingxuan, Bao, Weidong, Wang, Ji, Zhang, Dayu, Zhang, Xiongtao, Zhang, Yaohong

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I Know How You Move: Explicit Motion Estimation for Human Action Recognition Autor Shen, Zhongwei, Wu, Xiao-Jun, Li, Hui, Xu, Tianyang, Wu, Cong

“…Enabled by hierarchical convolutions and nonlinear mappings, recent action recognition studies have continuously boosted performance with spatiotemporal…”
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Pixel-level crack segmentation of tunnel lining segments based on an encoder-decoder network Autor HOU, Shaokang, OU, Zhigang, HUANG, Yuequn, LIU, Yaoru

“…Regular detection and repair for lining cracks are necessary to guarantee the safety and stability of tunnels. The development of computer vision has greatly…”
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RAFNet: Reparameterizable Across-Resolution Fusion Network for Real-Time Image Semantic Segmentation Autor Chen, Lei, Dai, Huhe, Zheng, Yuan

“…The demand to implement semantic segmentation networks on mobile devices has increased dramatically. However, existing real-time semantic segmentation methods…”
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A batch-wise LSTM-encoder decoder network for batch process monitoring Autor Ren, Jiayang, Ni, Dong

“…•Proposed a multi-layer recurrent neural network in the encoder–decoder structure and the corresponding monitoring method for batch process monitoring.•The…”
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SMART: Supervised multi-class image retargeting generative model based on a long-range sampling strategy Autor Cui, Jia, Jiang, Hao, Qi, Meng, Gu, Zhenyu, Lu, Hongju

“…Content-aware image retargeting (CAIR) techniques are crucial in multimedia processing for displaying images on various devices while preserving visually…”
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