LAMA - automatic model creation framework
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Updated
Apr 14, 2022 - Python
LAMA - automatic model creation framework
Multi-class metrics for Tensorflow
Experiments with UNET/FPN models and cityscapes/kitti datasets [Pytorch]
This repository contains the implementation for our work "Learning Topological Interactions for Multi-Class Medical Image Segmentation", accepted to ECCV 2022 (Oral)
Fast MOT base on yolo deepsort, support yolo3 and yolo4
Repository for KDD-Cup 2019 with Baidu. Big Data Science practical course @ LMU
A hyperspectral data set can be used for testing binary and multi-class change detection techniques.
This is an implementation of multi-class focal loss in PyTorch.
A hyperspectral data set can be used for testing binary and multi-class change detection techniques.
A jupyter notebook for analyzing and estimating with sklearn a multiclass classification problem for the Machine Learning (DD2421) course
Applying K Means and KNN on a multiclass dataset to make clusters and find nearest neighbours.
Pseudo-Inverse, Gradient-Stochastic-Steepest Descent, Logistic Regression and LDA-QDA
Multi-category perceptron training algorithm for digit classification
We investigated the performance of the Logistic and Multiclass Regression models and compared their accuracies to KNN. We compared Logistic Regression and KNN based on the "IMdB reviews" dataset, while Multiclass Regression and KNN were compared based on the "20 news groups" dataset.
This repository contains Python code for rice type detection using multiclass classification. The project leverages the MobileNetV2 architecture to classify six different types of rice: Arborio, Basmati, Ipsala, Jasmine, and Karacadag. The dataset used for training and evaluation can be found on Kaggle and consists of categorized rice images.
This repository represents a web app with a multi-class classification ML model which creates a segmented image of rocks and plain land.
I am interested in exploring machine learning techniques to predict the outcome of a European soccer game using game and player information collected. The generated predictive model will be able to predict the outcome of a game as Win, Loss or Draw for the home team. This model will use various attributes that are calculated each year for both h…
Multi Class Image Classification using Transfer learning with InceptionResNetV2
performance metrics for multi class in machine learning with codes
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