Lens imaging opposition-based learning. حسب Yuqi Xiong (12343771)

"…The algorithm integrates three key strategies: a precise population elimination strategy, which optimizes the population structure by eliminating individuals with low fitness and intelligently generating new ones; a lens imaging-based opposition learning strategy, which expands the exploration of the solution space through reflection and scaling to reduce the risk of local optima; and a boundary control strategy based on the best individual, which effectively constrains the search range to avoid inefficient searches and premature convergence. …"

Principle of lens imaging. حسب Yuefeng Leng (20678476)

Compare algorithm parameter settings. حسب Yuqi Xiong (12343771)

"…The algorithm integrates three key strategies: a precise population elimination strategy, which optimizes the population structure by eliminating individuals with low fitness and intelligently generating new ones; a lens imaging-based opposition learning strategy, which expands the exploration of the solution space through reflection and scaling to reduce the risk of local optima; and a boundary control strategy based on the best individual, which effectively constrains the search range to avoid inefficient searches and premature convergence. …"

Flowchart of low-light image enhancement based on MESBOA. حسب Yuqi Xiong (12343771)

Flowchart of low-light image enhancement based on MESBOA. حسب Yuqi Xiong (12343771)

-value on CEC2022 (dim = 20). حسب Yuqi Xiong (12343771)

"…The algorithm integrates three key strategies: a precise population elimination strategy, which optimizes the population structure by eliminating individuals with low fitness and intelligently generating new ones; a lens imaging-based opposition learning strategy, which expands the exploration of the solution space through reflection and scaling to reduce the risk of local optima; and a boundary control strategy based on the best individual, which effectively constrains the search range to avoid inefficient searches and premature convergence. …"

Precision elimination strategy. حسب Yuqi Xiong (12343771)

"…The algorithm integrates three key strategies: a precise population elimination strategy, which optimizes the population structure by eliminating individuals with low fitness and intelligently generating new ones; a lens imaging-based opposition learning strategy, which expands the exploration of the solution space through reflection and scaling to reduce the risk of local optima; and a boundary control strategy based on the best individual, which effectively constrains the search range to avoid inefficient searches and premature convergence. …"

Results of low-light image enhancement test. حسب Yuqi Xiong (12343771)

"…The algorithm integrates three key strategies: a precise population elimination strategy, which optimizes the population structure by eliminating individuals with low fitness and intelligently generating new ones; a lens imaging-based opposition learning strategy, which expands the exploration of the solution space through reflection and scaling to reduce the risk of local optima; and a boundary control strategy based on the best individual, which effectively constrains the search range to avoid inefficient searches and premature convergence. …"

-value on 23 benchmark functions (dim = 30). حسب Yuqi Xiong (12343771)

"…The algorithm integrates three key strategies: a precise population elimination strategy, which optimizes the population structure by eliminating individuals with low fitness and intelligently generating new ones; a lens imaging-based opposition learning strategy, which expands the exploration of the solution space through reflection and scaling to reduce the risk of local optima; and a boundary control strategy based on the best individual, which effectively constrains the search range to avoid inefficient searches and premature convergence. …"

Evaluation metrics obtained by SBOA and MESBOA. حسب Yuqi Xiong (12343771)

"…The algorithm integrates three key strategies: a precise population elimination strategy, which optimizes the population structure by eliminating individuals with low fitness and intelligently generating new ones; a lens imaging-based opposition learning strategy, which expands the exploration of the solution space through reflection and scaling to reduce the risk of local optima; and a boundary control strategy based on the best individual, which effectively constrains the search range to avoid inefficient searches and premature convergence. …"

Bayesian Spatial Binary Regression for Label Fusion in Structural Neuroimaging حسب D. Andrew Brown (6584837)

Thesis-RAMIS-Figs_Slides حسب Felipe Santibañez-Leal (10967991)

"…<br><br>Although the presented work was focused on 2-D binary channelized structures (geological facies), the applied principles are general and it can be extended to the characterization and recovery of other geological signals with spatial structure in under sampling contexts. …"

Image4_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF حسب Cédric Allier (4180903)

"…The networks have been trained to predict quantitative representation of the cell measurements that can be next translated into measurement lists with a local maxima algorithm. In this article, we discuss the performance and limitations of this novel deep learning-based quantification pipeline in comparison with a standard image processing solution. …"

Image1_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF حسب Cédric Allier (4180903)

"…The networks have been trained to predict quantitative representation of the cell measurements that can be next translated into measurement lists with a local maxima algorithm. In this article, we discuss the performance and limitations of this novel deep learning-based quantification pipeline in comparison with a standard image processing solution. …"

Image3_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF حسب Cédric Allier (4180903)

"…The networks have been trained to predict quantitative representation of the cell measurements that can be next translated into measurement lists with a local maxima algorithm. In this article, we discuss the performance and limitations of this novel deep learning-based quantification pipeline in comparison with a standard image processing solution. …"

Image2_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF حسب Cédric Allier (4180903)

"…The networks have been trained to predict quantitative representation of the cell measurements that can be next translated into measurement lists with a local maxima algorithm. In this article, we discuss the performance and limitations of this novel deep learning-based quantification pipeline in comparison with a standard image processing solution. …"

DataSheet1_CNN-Based Cell Analysis: From Image to Quantitative Representation.pdf حسب Cédric Allier (4180903)

"…The networks have been trained to predict quantitative representation of the cell measurements that can be next translated into measurement lists with a local maxima algorithm. In this article, we discuss the performance and limitations of this novel deep learning-based quantification pipeline in comparison with a standard image processing solution. …"

Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf حسب Cecilia Lindig-León (7889777)

"…And we propose two new multilabel uses of the Common Spatial Pattern (CSP) algorithm to optimize the signal-to-noise ratio, namely MC2CMI and MC2SMI approaches. …"

Segmentation, trace denoising and spike extraction framework. حسب Changjia Cai (10647521)

adjoint-elastic-registration.zip from Organ registration from partial surface data in augmented surgery from an optimal control perspective حسب Stéphane Cotin (3944129)

"…After a discussion about the existence of solutions, we analyse the necessary optimality conditions and use them to derive a suitable optimization algorithm. …"