Benchmark function graphs and convergence curves of different algorithms. by Guangwei Liu (181992)

Convergence curves of multimodal functions <i>f</i>₇. by Yu Li (183836)

Convergence curves of unimodal functions <i>f</i>₂. by Yu Li (183836)

Convergence curves of unimodal functions <i>f</i>₂. by Yu Li (183836)

Convergence curves of multimodal functions <i>f</i>₇. by Yu Li (183836)

Comparison of edge detector and CHT in detecting droplets. by Manibarathi Vaithiyanathan (6655274)

Pseudocode of the BBAC_I Algorithm. by Zezhi Lin (22521663)

Fig 1 - by Tobias Jonathan Pfeffer (12208658)

Comparison the results with and without Fourier Loss Function for Rain100H. by Chaobing Zheng (20896579)

Algorithm 1. by Jeffrey O. Agushaka (11326679)

Python cv coding screenshots of all developed fingerprints on distinct surfaces. by Nisha Yadav (366131)

Approximate energy consumed per particles in <i>nano Joules</i> (<i>nJ</i>) for various computation platforms and algorithms (A: first algorithm, B: second algorithm, C: third algo... by Abedalmuhdi Almomany (18547669)

Comparison of algorithm performance in ZDT1 and ZDT2 function tests. by Tao Dong (15551)

“…<p>Comparison of algorithm performance in ZDT1 and ZDT2 function tests.…”

DataSheet_1_Superiorization of projection algorithms for linearly constrained inverse radiotherapy treatment planning.pdf by Florian Barkmann (15152004)

“…Superiorization combines a feasibility-seeking projection algorithm with objective function reduction: The underlying projection algorithm is perturbed with gradient descent steps to steer the algorithm towards a solution with a lower objective function value compared to one obtained solely through feasibility-seeking.…”

DataSheet_1_Superiorization of projection algorithms for linearly constrained inverse radiotherapy treatment planning.pdf by Florian Barkmann (15152004)

“…Superiorization combines a feasibility-seeking projection algorithm with objective function reduction: The underlying projection algorithm is perturbed with gradient descent steps to steer the algorithm towards a solution with a lower objective function value compared to one obtained solely through feasibility-seeking.…”

DataSheet_1_Superiorization of projection algorithms for linearly constrained inverse radiotherapy treatment planning.pdf by Florian Barkmann (15152004)

“…Superiorization combines a feasibility-seeking projection algorithm with objective function reduction: The underlying projection algorithm is perturbed with gradient descent steps to steer the algorithm towards a solution with a lower objective function value compared to one obtained solely through feasibility-seeking.…”

<i>K</i>-CDFs: A Nonparametric Clustering Algorithm via Cumulative Distribution Function by Jicai Liu (11419050)

“…<p>We propose a novel partitioning clustering procedure based on the cumulative distribution function (CDF), called <i>K</i>-CDFs. For univariate data, the <i>K</i>-CDFs represent the cluster centers by empirical CDFs and assign each observation to the closest center measured by the Cram<math><mrow><mi>e</mi><mo>´</mo></mrow></math>r-von Mises distance. …”

Flowchart for Algorithm 1. by Sagvan Y. Musa (17797611)

Cumulative density function (CDF) of prediction error (PE, achieved spherical equivalent–formula predicted spherical equivalent) for the SRKT, Hoffer Q, Holladay1, Haigis (with opt... by Achim Langenbucher (3156741)

Subjects:

Convergence curves of the IMGO and comparison algorithms on functions <i>f</i>1−<i>f</i>7. by Ying Li (38224)

“…<p>Convergence curves of the IMGO and comparison algorithms on functions <i>f</i>1−<i>f</i>7.</p>…”