Search Results - Computer Learning AND Pattern Recognition::Uncertainty Management*

Energy management strategy for battery/supercapacitor hybrid electric city bus based on driving pattern recognition by Shi, Junzhe, Xu, Bin, Shen, Yimin, Wu, Jingbo

“… During the online operation, the proposed EMS executes the designed driving pattern recognition algorithm with V2C assistance to select optimal control rules…”
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Deep Stereo Using Adaptive Thin Volume Representation With Uncertainty Awareness by Cheng, Shuo, Xu, Zexiang, Zhu, Shilin, Li, Zhuwen, Li, Li Erran, Ramamoorthi, Ravi, Su, Hao

“…We present Uncertainty-aware Cascaded Stereo Network (UCS-Net) for 3D reconstruction from multiple RGB images. Multi-view stereo (MVS…”
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Rainbow Memory: Continual Learning with a Memory of Diverse Samples by Bang, Jihwan, Kim, Heesu, Yoo, YoungJoon, Ha, Jung-Woo, Choi, Jonghyun

“… To enhance the sample diversity in the memory, we propose a novel memory management strategy based on per-sample classification uncertainty and data augmentation, named Rainbow Memory (RM…”
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Parameter-free Online Test-time Adaptation by Boudiaf, Malik, Mueller, Romain, Ayed, Ismail Ben, Bertinetto, Luca

“…Training state-of-the-art vision models has become prohibitively expensive for researchers and practitioners. For the sake of accessibility and resource reuse,…”
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Geometric Anchor Correspondence Mining with Uncertainty Modeling for Universal Domain Adaptation by Chen, Liang, Lou, Yihang, He, Jianzhong, Bai, Tao, Deng, Minghua

“… Therefore, in this paper, we propose a Geometric anchor-guided Adversarial and conTrastive learning framework with uncErtainty modeling called GATE to alleviate these issues…”
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A novel algorithmic approach to model uncertainties associated with sustainable supply chain management using complex spherical fuzzy soft settings by Asghar, Ali, Khan, Khuram Ali, Rahman, Atiqe Ur, El-Morsy, Salwa

“…This study introduces the complex spherical fuzzy soft set (CSFSS), a sophisticated framework that deals with supplier selection uncertainties…”
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Handling the impact of feature uncertainties on SVM: A robust approach based on Sobol sensitivity analysis by Zouhri, Wahb, Homri, Lazhar, Dantan, Jean-Yves

“… SVM is a supervised machine learning method for pattern recognition whose performance depends on the definition of its hyperparameters and the quality of data…”
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Source-Free Progressive Graph Learning for Open-Set Domain Adaptation by Luo, Yadan, Wang, Zijian, Chen, Zhuoxiao, Huang, Zi, Baktashmotlagh, Mahsa

“…, and failure to accurately estimate model predictions' uncertainty. To address these limitations, the Progressive Graph Learning (PGL…”
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Exploring Data Aggregation in Policy Learning for Vision-Based Urban Autonomous Driving by Prakash, Aditya, Behl, Aseem, Ohn-Bar, Eshed, Chitta, Kashyap, Geiger, Andreas

“…Data aggregation techniques can significantly improve vision-based policy learning within a training environment, e.g…”
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Improving Fishing Pattern Detection from Satellite AIS Using Data Mining and Machine Learning by de Souza, Erico N., Boerder, Kristina, Matwin, Stan, Worm, Boris

“… While coastal fisheries in national waters are closely monitored in some countries, existing maps of fishing effort elsewhere are fraught with uncertainty, especially in remote areas and the High Seas…”
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Base belief function: an efficient method of conflict management by Wang, Yunjuan, Zhang, Kezhen, Deng, Yong

“…Dempster–Shafer evidence theory is widely used in many applications such as decision making and pattern recognition. However…”
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Geometry and Uncertainty-Aware 3D Point Cloud Class-Incremental Semantic Segmentation by Yang, Yuwei, Hayat, Munawar, Jin, Zhao, Ren, Chao, Lei, Yinjie

“…Despite the significant recent progress made on 3D point cloud semantic segmentation, the current methods require training data for all classes at once, and…”
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Digitalisation for nuclear waste management: predisposal and disposal by Kolditz, Olaf, Jacques, Diederik, Claret, Francis, Bertrand, Johan, Churakov, Sergey V., Debayle, Christophe, Diaconu, Daniela, Fuzik, Kateryna, Garcia, David, Graebling, Nico, Grambow, Bernd, Holt, Erika, Idiart, Andrés, Leira, Petter, Montoya, Vanessa, Niederleithinger, Ernst, Olin, Markus, Pfingsten, Wilfried, Prasianakis, Nikolaos I., Rink, Karsten, Samper, Javier, Szöke, István, Szöke, Réka, Theodon, Louise, Wendling, Jacques

“… Originally, data sciences were viewed to be well-suited, especially, for data-intensive applications such as image processing, pattern recognition, etc…”
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Transfer Knowledge from Head to Tail: Uncertainty Calibration under Long-tailed Distribution by Chen, Jiahao, Su, Bing

“…How to estimate the uncertainty of a given model is a crucial problem. Current calibration techniques treat different classes equally and thus implicitly assume…”
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Application of Deep Learning and Fuzzy Decision Support System in Residence Right Management by Fu, Liling

“… This work explores the utilization of Deep Learning and Fuzzy Decision Support Systems for Residence Right Management (DLFDSS-RRM…”
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Conformal deep forest for uncertainty-aware classification by Zhang, Jing, Qiu, Yunfei, Dong, Libo

“…Uncertainty in deep learning models significantly impacts their performance, robustness, and reliability, making explicit uncertainty quantification a critical research focus…”
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Active cluster annotation for wafer map pattern classification in semiconductor manufacturing by Shim, Jaewoong, Kang, Seokho, Cho, Sungzoon

“…•Active cluster annotation is proposed for wafer map pattern classification.•High-performance CNN is achieved with reduced annotation cost…”
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A novel framework for risk management of software projects by integrating a new COPRAS method under cloud model and machine learning algorithms by Haghighi, Mohammad Hossein, Ashrafi, Maryam

“… This new framework uses Machine Learning (ML) and Multi-Attribute Decision-Making under a cloud model to effectively manage uncertainty…”
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Multi-label classification by exploiting label correlations by Yu, Ying, Pedrycz, Witold, Miao, Duoqian

“…•By introducing the lower and upper approximation, the models consider the uncertainty during the process of classification…”
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EMG pattern recognition via Bayesian inference with scale mixture-based stochastic generative models by Furui, Akira, Igaue, Takuya, Tsuji, Toshio

“… This paper proposes an EMG pattern classification method incorporating a scale mixture-based generative model…”
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