Výsledky vyhľadávania - "prediction algorithms"

Secure Communication via Chaotic Synchronization Based on Reservoir Computing Autor Liu, Jiayue, Zhang, Jianguo, Wang, Yuncai

“…Information security occupies a very important part of national security. Chaos communication can provide high-level physical layer security, but its harsh…”
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VizWiz Grand Challenge: Answering Visual Questions from Blind People Autor Gurari, Danna, Li, Qing, Stangl, Abigale J., Guo, Anhong, Lin, Chi, Grauman, Kristen, Luo, Jiebo, Bigham, Jeffrey P.

“…The study of algorithms to automatically answer visual questions currently is motivated by visual question answering (VQA) datasets constructed in artificial…”
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Real-Time Scene Text Detection With Differentiable Binarization and Adaptive Scale Fusion Autor Liao, Minghui, Zou, Zhisheng, Wan, Zhaoyi, Yao, Cong, Bai, Xiang

“…Recently, segmentation-based scene text detection methods have drawn extensive attention in the scene text detection field, because of their superiority in…”
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Fairness in Graph Mining: A Survey Autor Dong, Yushun, Ma, Jing, Wang, Song, Chen, Chen, Li, Jundong

“…Graph mining algorithms have been playing a significant role in myriad fields over the years. However, despite their promising performance on various graph…”
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Learning to Adapt Structured Output Space for Semantic Segmentation Autor Tsai, Yi-Hsuan, Hung, Wei-Chih, Schulter, Samuel, Sohn, Kihyuk, Yang, Ming-Hsuan, Chandraker, Manmohan

“…Convolutional neural network-based approaches for semantic segmentation rely on supervision with pixel-level ground truth, but may not generalize well to…”
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Time-Varying Convex Optimization: Time-Structured Algorithms and Applications Autor Simonetto, Andrea, Dall'Anese, Emiliano, Paternain, Santiago, Leus, Geert, Giannakis, Georgios B.

“…Optimization underpins many of the challenges that science and technology face on a daily basis. Recent years have witnessed a major shift from traditional…”
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Graph-Based Semi-Supervised Learning: A Comprehensive Review Autor Song, Zixing, Yang, Xiangli, Xu, Zenglin, King, Irwin

“…Semi-supervised learning (SSL) has tremendous value in practice due to the utilization of both labeled and unlabelled data. An essential class of SSL methods,…”
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Machine Remaining Useful Life Prediction via an Attention-Based Deep Learning Approach Autor Chen, Zhenghua, Wu, Min, Zhao, Rui, Guretno, Feri, Yan, Ruqiang, Li, Xiaoli

“…For prognostics and health management of mechanical systems, a core task is to predict the machine remaining useful life (RUL). Currently, deep structures with…”
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Structure-Measure: A New Way to Evaluate Foreground Maps Autor Deng-Ping Fan, Ming-Ming Cheng, Yun Liu, Tao Li, Borji, Ali

“…Foreground map evaluation is crucial for gauging the progress of object segmentation algorithms, in particular in the field of salient object detection where…”
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Robust Point Cloud Registration Framework Based on Deep Graph Matching Autor Fu, Kexue, Luo, Jiazheng, Luo, Xiaoyuan, Liu, Shaolei, Zhang, Chenxi, Wang, Manning

“…3D point cloud registration is a fundamental problem in computer vision and robotics. Recently, learning-based point cloud registration methods have made great…”
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Large-scale water quality prediction with integrated deep neural network Autor Bi, Jing, Lin, Yongze, Dong, Quanxi, Yuan, Haitao, Zhou, MengChu

“…Water environment time series prediction is important to efficient water resource management. Traditional water quality prediction is mainly based on linear…”
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An Efficient Implementation of the Generalized Labeled Multi-Bernoulli Filter Autor Vo, Ba-Ngu, Vo, Ba-Tuong, Hoang, Hung Gia

“…This paper proposes an efficient implementation of the generalized labeled multi-Bernoulli (GLMB) filter by combining the prediction and update into a single…”
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Mobility-Aware Cooperative Caching in Vehicular Edge Computing Based on Asynchronous Federated and Deep Reinforcement Learning Autor Wu, Qiong, Zhao, Yu, Fan, Qiang, Fan, Pingyi, Wang, Jiangzhou, Zhang, Cui

“…Vehicular edge computing (VEC) can learn and cache most popular contents for vehicular users (VUs) in the roadside units (RSUs) to support real-time vehicular…”
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Challenges in KNN Classification Autor Zhang, Shichao

“…The KNN algorithm is one of the most popular data mining algorithms. It has been widely and successfully applied to data analysis applications across a variety…”
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Two Easy-to-Use Scores to Identify Acute Geriatric Patients With High Rehabilitation Success Autor Gutheil, Julian, Göbel, Bettina, Fasching, Peter, Iglseder, Bernhard, Wenkstetten-Holub, Alfa, Pinter, Georg, Müller, Walter, Mrak, Peter, Boulgaropoulos, Beate, Huber, Joakim, Feichtner, Franz

“…Many geriatric patients who would benefit from a stay in an acute geriatric ward (AGW) are not identified because of the lack of objective and standardized…”
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Interpretable Explanations of Black Boxes by Meaningful Perturbation Autor Fong, Ruth C., Vedaldi, Andrea

“…As machine learning algorithms are increasingly applied to high impact yet high risk tasks, such as medical diagnosis or autonomous driving, it is critical…”
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Adaptive Speed Control of PMSM Drive System Based a New Sliding-Mode Reaching Law Autor Junejo, Abdul Khalique, Xu, Wei, Mu, Chaoxu, Ismail, Moustafa Magdi, Liu, Yi

“…In order to enhance the speed control performance of the permanent magnet synchronous motor (PMSM) with internal and external disturbances, a new adaptive…”
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Model Predictive Control for Power Converters and Drives: Advances and Trends Autor Vazquez, Sergio, Rodriguez, Jose, Rivera, Marco, Franquelo, Leopoldo G., Norambuena, Margarita

“…Model predictive control (MPC) is a very attractive solution for controlling power electronic converters. The aim of this paper is to present and discuss the…”
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Model Predictive Current Control for PMSM Drives With Parameter Robustness Improvement Autor Zhang, Xiaoguang, Zhang, Liang, Zhang, Yongchang

“…In order to solve the parameter dependence problem in model predictive control, an improved model predictive current control (MPCC) method based on the…”
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Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond Autor Liu, Fanghui, Huang, Xiaolin, Chen, Yudong, Suykens, Johan A. K.

“…The class of random features is one of the most popular techniques to speed up kernel methods in large-scale problems. Related works have been recognized by…”
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