Binary encoding scheme. حسب Binh Thanh Dang (12368831)

QSAR model for predicting neuraminidase inhibitors of influenza A viruses (H1N1) based on adaptive grasshopper optimization algorithm حسب Z.Y. Algamal (5547620)

"…Obtaining a reliable QSAR model with few descriptors is an essential procedure in chemometrics. The binary grasshopper optimization algorithm (BGOA) is a new meta-heuristic optimization algorithm, which has been used successfully to perform feature selection. …"

ROC curve for binary classification. حسب Nicodemus Songose Awarayi (18414494)

"…The study introduced a scheme for enhancing images to improve the quality of the datasets. Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …"

Confusion matrix for binary classification. حسب Nicodemus Songose Awarayi (18414494)

"…The study introduced a scheme for enhancing images to improve the quality of the datasets. Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …"

Datasets and their properties. حسب Olaide N. Oyelade (14047002)

"…However, the underlying deficiency of the single binary optimizer is transferred to the quality of the features selected. …"

Parameter settings. حسب Olaide N. Oyelade (14047002)

"…However, the underlying deficiency of the single binary optimizer is transferred to the quality of the features selected. …"

Our proposed framework. حسب Abdullah Sheneamer (19169236)

"…Various approaches have been used to identify diseases, including image processing and sophisticated algorithms. The most effective method of disease identification from crops is automatic detection using methods of image processing and classification algorithms for the diseases to be categorised based on different picture attributes. …"

Tomato dataset results. حسب Abdullah Sheneamer (19169236)

"…Various approaches have been used to identify diseases, including image processing and sophisticated algorithms. The most effective method of disease identification from crops is automatic detection using methods of image processing and classification algorithms for the diseases to be categorised based on different picture attributes. …"

Plant village dataset results. حسب Abdullah Sheneamer (19169236)

"…Various approaches have been used to identify diseases, including image processing and sophisticated algorithms. The most effective method of disease identification from crops is automatic detection using methods of image processing and classification algorithms for the diseases to be categorised based on different picture attributes. …"

Stacking five models ROC value. حسب Abdullah Sheneamer (19169236)

"…Various approaches have been used to identify diseases, including image processing and sophisticated algorithms. The most effective method of disease identification from crops is automatic detection using methods of image processing and classification algorithms for the diseases to be categorised based on different picture attributes. …"

Grape dataset results. حسب Abdullah Sheneamer (19169236)

"…Various approaches have been used to identify diseases, including image processing and sophisticated algorithms. The most effective method of disease identification from crops is automatic detection using methods of image processing and classification algorithms for the diseases to be categorised based on different picture attributes. …"

Ensemble deep learning classifiers results. حسب Abdullah Sheneamer (19169236)

"…Various approaches have been used to identify diseases, including image processing and sophisticated algorithms. The most effective method of disease identification from crops is automatic detection using methods of image processing and classification algorithms for the diseases to be categorised based on different picture attributes. …"

Hyberparameters of CNN architectures. حسب Abdullah Sheneamer (19169236)

"…Various approaches have been used to identify diseases, including image processing and sophisticated algorithms. The most effective method of disease identification from crops is automatic detection using methods of image processing and classification algorithms for the diseases to be categorised based on different picture attributes. …"

Peach dataset results. حسب Abdullah Sheneamer (19169236)

"…Various approaches have been used to identify diseases, including image processing and sophisticated algorithms. The most effective method of disease identification from crops is automatic detection using methods of image processing and classification algorithms for the diseases to be categorised based on different picture attributes. …"

Various fruits disease datasets [25]. حسب Abdullah Sheneamer (19169236)

"…Various approaches have been used to identify diseases, including image processing and sophisticated algorithms. The most effective method of disease identification from crops is automatic detection using methods of image processing and classification algorithms for the diseases to be categorised based on different picture attributes. …"

Apple dataset results. حسب Abdullah Sheneamer (19169236)

"…Various approaches have been used to identify diseases, including image processing and sophisticated algorithms. The most effective method of disease identification from crops is automatic detection using methods of image processing and classification algorithms for the diseases to be categorised based on different picture attributes. …"

Confusion matrix of stacking five models. حسب Abdullah Sheneamer (19169236)

"…Various approaches have been used to identify diseases, including image processing and sophisticated algorithms. The most effective method of disease identification from crops is automatic detection using methods of image processing and classification algorithms for the diseases to be categorised based on different picture attributes. …"

Identification and quantitation of clinically relevant microbes in patient samples: Comparison of three k-mer based classifiers for speed, accuracy, and sensitivity حسب George S. Watts (7962206)

"…We tested the accuracy, sensitivity, and resource requirements of three top metagenomic taxonomic classifiers that use fast k-mer based algorithms: Centrifuge, CLARK, and KrakenUniq. …"

SHAP bar plot. حسب Meng Cao (105914)

"…</p><p>Results</p><p>Logistic regression analysis identified age, hemoglobin concentration, education level, and social participation as significant factors influencing CI. Models based on NNET, RF, LR, and SVM algorithms were developed, achieving AUC of 0.918, 0.889, 0.872, and 0.760, respectively, on the test set. …"

Sample screening flowchart. حسب Meng Cao (105914)

"…</p><p>Results</p><p>Logistic regression analysis identified age, hemoglobin concentration, education level, and social participation as significant factors influencing CI. Models based on NNET, RF, LR, and SVM algorithms were developed, achieving AUC of 0.918, 0.889, 0.872, and 0.760, respectively, on the test set. …"