Dynamic Energy Sparse Self-Attention Based on Informer for Remaining Useful Life of Rolling Bearings by Cheng Shi, Qifei Li, Hui Chen, Yuanwei Song, Qianqi Le

“…To address these issues, this paper proposes the dynamic energy sparse self-attention model based on Informer. The proposed model uses the auto-reassignment transform to extract more accurate features from the raw vibration signals, and the dynamic energy sparse self-attention mechanism adapts the attention weights based on the energy distribution. …”
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Example-Based Super-Resolution Image Reconstruction for Positron Emission Tomography Using Sparse Coding by Xue Ren, Soo-Jin Lee

“…This paper presents example-based methods for super-resolution (SR) reconstruction from a single set of low-resolution projections (or a sinogram) in positron emission tomography (PET). …”
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Fast Low Rank and Sparse Decomposition Based on Greedy Bilateral Smoothing for Infrared Small Target Detection by Yan-Shan Zhang, Ze-Yin Li, Dong-Dong Pang, Lu-Yao Wang, Cheng-Jun Wu, Kang Duan, Jun-Ming Gao

“…To address this issue, this study presents a fast and robust low rank and sparse decomposition algorithm for infrared small target detection. …”
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SFT-GAN: Sparse Fast Transformer Fusion Method Based on GAN for Remote Sensing Spatiotemporal Fusion by Zhaoxu Ma, Wenxing Bao, Wei Feng, Xiaowu Zhang, Xuan Ma, Kewen Qu

“…Overall, this approach presents a new paradigm for balancing accuracy and efficiency in spatiotemporal fusion.…”
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Constraint Sparse Maximum Correntropy Beamforming Algorithm against Impulsive Noise to Improve the Performance of GNSS Signal Acquisition by Haichuan Zhang, Fangling Zeng

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Estimating vertical land motion-adjusted sea level rise in a data-sparse and vulnerable coastal region by Ashraf Dewan, Hardik Jain, Md Alamgir Hossain, Mohammed Sarfaraz Gani Adnan, Md Redowan Mahmud

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A Novel Interrupted-Sampling Repeater Jamming Suppression Method Based on Time-Frequency Analysis and Target Sparse Reconstruction by Zijian Wang, Jiamu Li, Wenbo Yu, Yunhua Luo, Zhongjun Yu

“…Finally, guided by the identification result, the real targets can be retained and reconstructed by adaptive filtering in the sparse domain to realize ISRJ suppression. …”
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Automated sparse feature selection in high-dimensional proteomics data via 1-bit compressed sensing and K-Medoids clustering by FuDong Wen, Yue Su, Dan Liu, YuPeng Wang, MeiNa Liu

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Survey on Replay-Based Continual Learning and Empirical Validation on Feasibility in Diverse Edge Devices Using a Representative Method by Heon-Sung Park, Hyeon-Chang Chu, Min-Kyung Sung, Chaewoon Kim, Jeongwon Lee, Dae-Won Kim, Jaesung Lee

“…Consequently, designing strategies that balance the preservation of past knowledge with rapid and cost-effective updates of model parameters has become a critical consideration in on-device continual learning. This paper presents an empirical survey of replay-based continual learning studies, considering the nearest class mean classifier with replay-based sparse weight updates as a representative method for validating the feasibility of diverse edge devices. …”
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Graph-aware isomorphic attention for adaptive dynamics in transformers by Markus J. Buehler

“…We expand the concept of graph-aware attention to introduce sparse-GIN-attention, a fine-tuning approach that enhances the adaptability of pre-trained foundational models with minimal computational overhead, endowing them with graph-aware capabilities. …”
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Fuzzy model-based analysis of user feedback for product development insights by Anna Sudár, Borbála Berki, Ildikó Horváth

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EDRNet: Edge-Enhanced Dynamic Routing Adaptive for Depth Completion by Fuyun Sun, Baoquan Li, Qiaomei Zhang

“…Secondly, we design a Sparse Adaptive Dynamic Routing Transformer block called SADRT, which can effectively combine the global modelling capability of the Transformer and the local feature extraction capability of CNN. …”
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A novel mosaic adaptive attention network for multispectral imaging reconstruction by Zhongqiang Zhang, Fanyang Meng, Dahua Gao, Haoyong Li

“…By sampling the spectra with random broadband filter-based MSFA, more spectral information is preserved in the generated spectral mosaic images. We further present an end-to-end mosaic adaptive attention network (MAAN) for multispectral image reconstruction. …”
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A Robust Direction-of-Arrival (DOA) Estimator for Weak Targets Based on a Dimension-Reduced Matrix Filter with Deep Nulling and Multiple-Measurement-Vector Orthogonal Matching Purs... by Shoudong Wang, Haozhong Wang, Zhaoxiang Bian, Susu Chen, Penghua Song, Bolin Su, Wei Gao

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Compressive-Sensing-Based Video Codec by Autoregressive Prediction and Adaptive Residual Recovery by Ran Li, Hongbing Liu, Rui Xue, Yanling Li

“…Firstly, the proposed algorithm uses the temporal autoregressive (AR) model to generate the Side Information (SI) of video frame, and next it recovers the residual between the original frame and the corresponding SI. To exploit the sparse property of residual with locally varying statistics, the Principle Component Analysis (PCA) is used to learn online the transform matrix adapting to residual structures. …”
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Adaptive Prediction of a Random Process Using a Sequential Regression Algorithm by Vladimir A. Golovkov

“…The results of numerical calculations and the implementation of random process, its optimal and adaptive prediction obtained during the simulation were presented. …”
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Model-based iterative reconstruction with adaptive regularization for artifact reduction in electron tomography by Singanallur Venkatakrishnan, Obaidullah Rahman, Lynda Amichi, Jose D. Arregui-Mena, Haoran Yu, David A. Cullen, Amirkoushyar Ziabari

“…These artifacts lead to errors in the downstream characterization affecting extraction of critical features such as the size of the metal particles, their distribution and the volume of the lighter support regions. In this paper, we present a two-stage algorithm based on metal artifact reduction, utilizing model-based iterative reconstruction methods with adaptive adjustment of regularization parameters. …”
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Learning in presence of class imbalance and class overlapping by using one-class SVM and undersampling technique by Debashree Devi, Saroj K. Biswas, Biswajit Purkayastha

“…In this study, an in-depth analysis of the effects of class imbalance and class overlapping in conventional learning models has been presented. A data level approach is adapted with one-class SVM-based anomaly detection to detect the cases of data overlapping while an adapted Tomek-link undersampling algorithm is defined to treat both overlapped and imbalanced cases. …”
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LAST-PAIN: Learning Adaptive Spike Thresholds for Low Back Pain Biosignals Classification by Freek Hens, Mohammad Mahdi Dehshibi, Leila Bagheriye, Ana Tajadura-Jimenez, Mahyar Shahsavari

“…The LAST encoder learns adaptive thresholds to transform continuous signals of varying dimensionality-ranging from time series data to high dimensional tensors-into sparse spike trains. …”
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Continuous Adaptive Stabilization of the Unstable Period-1 Orbit of the Fractional Difference Logistic Map by Ernestas Uzdila, Inga Telksniene, Tadas Telksnys, Minvydas Ragulskis

“…A continuous adaptive stabilization technique for the unstable period-1 orbit of the fractional difference logistic map is presented in this paper. …”
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