As the dataset had an uneven distribution of class information, pre-processing processes including data reduction and augmentation were required to correct the problem In addition, the classification process was carried out with the assistance of three widely used convolutional neural network models. We...
https://www.kaggle.com/datasets/masoudnickparvar/brain-tumor-mri-dataset. References Zhao G, Feng Q, Chen C, Zhou Z, Yu Y (2021) Diagnose like a radiologist: hybrid neuro-probabilistic reasoning for attribute-based medical image diagnosis. IEEE Trans Pattern Anal Mach Intell 44(11):7400–...
Data Availability (2022) Retrieved April 1, 2024, from https://www.kaggle.com/datasets/uraninjo/augmented-alzheimer-mri-dataset Özkaraca O, Bağrıaçık Oİ, Gürüler H, Khan F, Hussain J, Khan J, Ue L (2023) Multiple brain tumor classification with dense CNN architecture usi...
Their utilized dataset is from the Kaggle platform. Podder, Kanchon Kanti, et al. [11], demonstrated the classification of BdSL alphabets as well as numerals utilizing deep CNN models and they achieved 99.99% accuracy. In [12], the authors proposed deep CNN-based Bangla sign language ...
Furthermore, to validate the robustness of our approach, we conduct experiments on four diverse datasets such as MSID (Multi Skin Infection dataset), gastrointestinal multi-infection, Kaggle MRI multiclass, and BR35H MRI binary class dataset. The proposed model consistently maintains high performance...
We have used CNN for multiclass image classification to determine the input medical image is brain, chest or knee and then SVM is used for binary classification to determine whether that input image is detected with the disease or not. Three different datasets from Kaggle are used: Brain Tumor...
For this study, we utilize the dry bean dataset from Kaggle for classification within a FL setup. The study evaluates the performance of the aforementioned FL algorithms in the context of multiclass classification, comparing them against traditional centralized models. To test the robustness of FL ...
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Explore and run machine learning code with Kaggle Notebooks | Using data from Amazon.com - Employee Access Challenge
Explore and run machine learning code with Kaggle Notebooks | Using data from Dermatology Dataset (Multi-class classification)