Combining flash memory and FPGAs to efficiently implement a massively parallel algorithm for content-based image retrival - Chikhi, Derrien, et al. () Citation Context ...] that operates in the wavelet domain and uses partial distance search to accelerate the classification process. The resulting...
We need to pre-process our data before we can use it for modeling. Let’s check if the data has any missing values: sum(is.na(train)) #[1] 86 Next, let us use Caret to impute these missing values using KNN algorithm. We will predict these missing values based on other at...
Now that we have the building blocks for a kNN model, let’s look at the Perceptron algorithm. 1.2 Sub-model #2: Perceptron The model for the Perceptron algorithm is a set of weights learned from the training data. In order to train the weights, many predictions need to be made on the...
Five algorithms were used to build a machine learning model to compare and find the best algorithm among them to help with diagnosis and predictions. The five algorithms are described in Table 12 (naive Bayes (NB), k-nearest neighbors (KNN), support vector machine (SVM), random forest (RF...
Click on the name of algorithm to check the parameters Use the opts to set the specific parameters No.AbbreviationNameSupport 09 'gmm' Gaussian Mixture Model Multi-class 08 'knn' K-nearest Neighbor Multi-class 07 'msvm' Multi-class Support Vector Machine Multi-class 06 'svm' Support Vector ...
* `B` [k-NN](src/algorithms/ml/knn) - k-nearest neighbors classification algorithm * `B` [k-Means](src/algorithms/ml/k-means) - k-Means clustering algorithm * **Image Processing** * `B` [Seam Carving](src/algorithms/image-processing/seam-carving) - content-aware image resizing algori...
Measurement is the most important process of the proposed fault diagnosis algorithm. After this process, we can obtain a special RMS voltage UkN, which is the key for deciding fault localization variables. In addition, the details of this process are explained in Section 2.3. The second step ...
Routine scanner loading needed to be as easy, fast, and straightforward as possible for the laboratory technicians. In order to have the automatic profile feature in addition to automatic tissue detection obtained by an AI algorithm in the scanner control software, it was very important to scan ...