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DeepLeukemiaNet
An Efficient Approach for Segmentation and Classification of Acute Lymphoblastic Leukemia via Optimized Spike-based NetworkDeep-Residual-COVID-Net
This program is belong to A Novel Method for Detection of COVID-19 Cases Using Deep Residual Neural Network research article.scikit_learn_classifiers
accuracy of the scikit_learn classifiersNeural-Networks
in this section we build a simple neural net using pythonConvolutional_Neural_Network
object detection using Convolutional Neural Network (using only numpy lib)Contrastive-Language-Image-Pretraining-Model-CLIP
LogisticRegressionModel
creating a LogisticRegressionModel for classification of 32000 of employee dataPlant-Image-Classification
In this project we aimed to classify species of plants, which are divided into categories according to the species of the plant to which they belong. Being a classification problem, given an image, the goal is to predict the correct class label.Acute-Lymphoblastic-Leukemia-Detection-using-ResNet50
Development of Classification Model for Acute Lymphoblastic Leukemia Detection using ResNet50TimeSeriesClassification
In this project, we aimed to correctly classify samples in the multivariate time series format. In other words, since this is a classification problem, the objective is to correctly map the information contained in the features calculated over time to their labels.Love Open Source and this site? Check out how you can help us