Collaborative hunting behavior. by Chenyi Zhu (9383370)

Subjects: “…continuous optimization algorithm…”

IRBMO vs. variant comparison adaptation data. by Chenyi Zhu (9383370)

Subjects: “…continuous optimization algorithm…”

AI Algorithm Workflow: Image pre-processing with highest pixel intensity identification (a), RGB channel breakdown, Fluorescence isolation and grayscale conversion (b), Computation... by Gareth Gallagher (20874910)

IHML: Incremental Heuristic Meta-Learner by Onur Karadeli (20427293)

“…This study introduces the IHML: Incremental Heuristic Meta-Learner, a novel meta-learning algorithm for classification tasks. By leveraging a variety of base-learners with distinct learning dynamics, such as Gaussian, tree, and instance, IHML offers a comprehensive solution adaptable to different data characteristics. …”

Feature quantity and number. by Jizhong Wang (7441697)

“…Finally, a transformer diagnostic model based on SSA-LightGBM was constructed, and the ten fold cross validation method was used to verify the classification ability of the model. The experimental results show that the SSA-LightGBM model proposed in this paper has an average fault diagnosis accuracy of 93.6% after SSA algorithm optimization, which is 3.6% higher than before optimization. …”

Diagnostic accuracy of different models. by Jizhong Wang (7441697)

“…Finally, a transformer diagnostic model based on SSA-LightGBM was constructed, and the ten fold cross validation method was used to verify the classification ability of the model. The experimental results show that the SSA-LightGBM model proposed in this paper has an average fault diagnosis accuracy of 93.6% after SSA algorithm optimization, which is 3.6% higher than before optimization. …”

Scatter diagram of different principal elements. by Jizhong Wang (7441697)

“…Finally, a transformer diagnostic model based on SSA-LightGBM was constructed, and the ten fold cross validation method was used to verify the classification ability of the model. The experimental results show that the SSA-LightGBM model proposed in this paper has an average fault diagnosis accuracy of 93.6% after SSA algorithm optimization, which is 3.6% higher than before optimization. …”

Key parameters of LightGBM. by Jizhong Wang (7441697)

“…Finally, a transformer diagnostic model based on SSA-LightGBM was constructed, and the ten fold cross validation method was used to verify the classification ability of the model. The experimental results show that the SSA-LightGBM model proposed in this paper has an average fault diagnosis accuracy of 93.6% after SSA algorithm optimization, which is 3.6% higher than before optimization. …”

Multi-model fault diagnosis results. by Jizhong Wang (7441697)

“…Finally, a transformer diagnostic model based on SSA-LightGBM was constructed, and the ten fold cross validation method was used to verify the classification ability of the model. The experimental results show that the SSA-LightGBM model proposed in this paper has an average fault diagnosis accuracy of 93.6% after SSA algorithm optimization, which is 3.6% higher than before optimization. …”

Algorithm ranking based on results from both magnitude and shape cohorts. by Arshiya Mariam (10190281)

“…<p>(A-B) and (C-D) show the average rank and Adjusted Rand Index (ARI), respectively, for all 30 algorithms across all cohorts. …”

Effect of post-processing threshold and algorithms performance on the species composition estimation. by Valentine Fleuré (12822137)

“…Each panel gathers results for a detection algorithm (recall in column and precision in row) and a classification algorithm (color corresponding to its accuracy). …”

Effect of post-processing threshold and algorithms performance on the communities abundance-structure estimation. by Valentine Fleuré (12822137)

“…Each panel gathers results for a detection algorithm (recall in column and precision in row) and a classification algorithm (color corresponding to its accuracy). …”

Histogram equalization process of rhinoceros images (adaptive histogram equalization and global histogram equalization). by Manqi Li (22633830)

Image preprocessing results of rhinoceros images (original, grayscale, threshold segmentation, and mean filtering). by Manqi Li (22633830)

Low-energy electron microscopy intensity-voltage data – factorization, sparse sampling, and classification by Francesco Masia (19079246)

“…Similarly the results of the classification algorithm are available as tiff images, while the average concentration and spectra calculated over the training and testing regions are given as ascii data. …”

Selected examples from the ImageNet-Hard dataset. by Ebrahim Parcham (20700216)

“…<div><p>Many artificial intelligence (AI) algorithms struggle to adapt effectively in dynamic real-world scenarios, such as complex classification tasks and object relationship extraction, due to their predictable but non-adaptive behavior. …”

Last layers of Grad-CAM in HybridBranchNetV2. by Ebrahim Parcham (20700216)

“…<div><p>Many artificial intelligence (AI) algorithms struggle to adapt effectively in dynamic real-world scenarios, such as complex classification tasks and object relationship extraction, due to their predictable but non-adaptive behavior. …”

Effect of video processing rate and algorithms performance on the estimation of the abundance-structure of simulated communities. by Valentine Fleuré (12822137)

“…Each dot represents the average over the 10 simulations with corresponding standard error as vertical bars. …”

Effect of video processing rate and algorithms performance on the estimation of species composition of simulated communities. by Valentine Fleuré (12822137)

“…Each dot represents the average over the 10 simulations with corresponding standard error as vertical bars. …”

SEM cervix cell images. by Sevcan AYTAÇ (20685197)

“…Homogeneity, contrast, angular second moment, entropy, mean, standard deviation, correlation, cluster prominence, dissimilarity, and cluster shade values have been calculated for each of these one approximate and three detail coefficients. The classification rate found by the averages of the results obtained from the DWTF_JSD, DWTF_HD and DWTF_TD algorithms for AFM and SEM cervix images are 98.29% and 97.10%, respectively. …”