Urgent versus nonurgent binary classification performance. حسب Kyung Won Kwon (18150416)

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

"…The proposed model yielded notable results, such as an accuracy of 93.45% and an area under the curve value of 0.99 when trained on the three classes. The model further showed superior results on binary classification compared with existing methods. …"

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

"…The proposed model yielded notable results, such as an accuracy of 93.45% and an area under the curve value of 0.99 when trained on the three classes. The model further showed superior results on binary classification compared with existing methods. …"

Graphical comparison of binary class lung cancer classification with different approaches. حسب Md. Sabbir Hossain (9958939)

الموضوعات:

Applying the proposed image enhancement algorithm. حسب Nicodemus Songose Awarayi (18414494)

Performance of the proposed method for binary classification of lung cancer. حسب Md. Sabbir Hossain (9958939)

الموضوعات:

The illustration depicts our CQ-CNN architecture for binary image classification. حسب Mominul Islam (3513758)

(a) Accuracy and (b) loss curves of training and validation during binary class classification for 512 features extracted by the CNN. حسب Md. Sabbir Hossain (9958939)

الموضوعات:

ROC curves of the proposed method for binary class classification: (A) GNB, (B) GBM, (C) KNN, (D) SVM, (E) RF, and (F) Ensemble learning. حسب Md. Sabbir Hossain (9958939)

الموضوعات:

Visualization of color maps using Grad-CAM for different lung cancer classes. حسب Md. Sabbir Hossain (9958939)

الموضوعات:

Performance of the individual and proposed methods for multiclass classification of lung cancer. حسب Md. Sabbir Hossain (9958939)

الموضوعات:

Graphical comparison of multiclass lung cancer classification with different approaches. حسب Md. Sabbir Hossain (9958939)

الموضوعات:

(A) Accuracy and (B) loss of training and validation sets of multiclass classification using CNN. حسب Md. Sabbir Hossain (9958939)

الموضوعات:

Structure of the proposed hybrid CNN-SVD-based ensemble model for lung cancer classification. حسب Md. Sabbir Hossain (9958939)

الموضوعات:

Testing results for classifying AD, MCI and NC. حسب Nicodemus Songose Awarayi (18414494)

"…The proposed model yielded notable results, such as an accuracy of 93.45% and an area under the curve value of 0.99 when trained on the three classes. The model further showed superior results on binary classification compared with existing methods. …"

Summary of existing CNN models. حسب Nicodemus Songose Awarayi (18414494)

"…The proposed model yielded notable results, such as an accuracy of 93.45% and an area under the curve value of 0.99 when trained on the three classes. The model further showed superior results on binary classification compared with existing methods. …"

<b>BRISC: Annotated Dataset for Brain Tumor Segmentation and Classification</b> حسب BRISC Dataset (22559540)

"…<p dir="ltr"><b>BRISC 2025 — Brain Tumor MRI Dataset</b></p><p dir="ltr">BRISC (BRain tumor Image Segmentation & Classification) — a curated, expert-annotated T1 MRI dataset for multi-class brain tumor classification and pixel-wise segmentation.…"

Dataset 1: Zip file containing the figures of the presented methods and results in jpeg files حسب Suchismita Behera (22027316)

ROC curves of the proposed method for multiclass classification: (A) GNB, (B) GBM, (C) KNN, (D) SVM, (E) RF, and (F) Ensemble learning. حسب Md. Sabbir Hossain (9958939)

الموضوعات:

Lung cancer CT images before and after pre-processing. حسب Md. Sabbir Hossain (9958939)

الموضوعات: