alinowshad/Deep-Residual-COVID-Net

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Created about 4 years ago
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alinowshad/Deep-Residual-COVID-Net

alinowshad

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This program is belong to A Novel Method for Detection of COVID-19 Cases Using Deep Residual Neural Network research article.

DeepLeukemiaNet

An Efficient Approach for Segmentation and Classification of Acute Lymphoblastic Leukemia via Optimized Spike-based Network

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scikit_learn_classifiers

accuracy of the scikit_learn classifiers

Neural-Networks

in this section we build a simple neural net using python

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Convolutional_Neural_Network

object detection using Convolutional Neural Network (using only numpy lib)

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Contrastive-Language-Image-Pretraining-Model-CLIP

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LogisticRegressionModel

creating a LogisticRegressionModel for classification of 32000 of employee data

Prediction-Of-Coronavirus-Confirmed-White-Linear-Regression

we use GRADIENT DESCENT to find the best fitting line

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Plant-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.

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Acute-Lymphoblastic-Leukemia-Detection-using-ResNet50

Development of Classification Model for Acute Lymphoblastic Leukemia Detection using ResNet50

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TimeSeriesClassification

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.

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