The MSMO is used for on-chip training. The circuit of the largest absolute value decision is designed to avoid the unclassifiable problem in the OAO multiclass classification. The designed system is implemented on a field-programmable gate array (FPGA) platform and evaluated using the publicly ...
To boost the classification accuracy of support-vector-machines(SVM), we propose an algorithm with evolutionary multiple kernels(EMK), based on the genetic programming(GP). In this algorithm, each individual represents a multiple kernel function, and is encoded by the tree-structure for enhancing ...
This paper proposes a novel hybrid algorithm ABCE - the combination of ABC algorithm and a classifier ensemble (CE). A classifier ensemble consisting of Support Vector Machine (SVM), Decision Tree and Nave Bayes, performs the task of classification and ABCE is used as a feature selector to ...
This paper proposes the use of Support Vector Machine (SVM), a recently introduced machine learning tool, in the classifier design stage of PR system. The developed PR system is implemented in IEEE standard test systems for SSA and classification. The performance of SVM classifier is compared ...
(SVC) algorithm for classification, employing a 6-degree polynomial kernel (\(K(x_i, y_j) = (\gamma (x_i^T y_j) + c)^6\)). The parameter ’c’ in the kernel function serves as a free parameter that governs the influence of higher-order terms relative to lower-order terms ...
(SVC) algorithm for classification, employing a 6-degree polynomial kernel (\(K(x_i, y_j) = (\gamma (x_i^T y_j) + c)^6\)). The parameter ’c’ in the kernel function serves as a free parameter that governs the influence of higher-order terms relative to lower-order terms ...
Fig. 3 illustrates the overall process of applying the proposed fine-grained algorithm for evaluating an incoming packet. As can be seen, the process starts with a new incoming packet. First, two types of features, contextual and content-based, are extracted from the packet (step 1). The co...
The goal of this article was to review the basic concepts and methodologies used in PR. The adopted approach was to focus on the major stages followed for the design of aPR systemfor theautomatic classificationof patterns into one from a number of classes. More emphasis was given on theclassi...
- Artificial Neural Networks (ANN): Inspired by the biological neural system, ANNs are the most used supervised learning algorithm, designed for various tasks such as classification, regression, signal processing, time series forecasting, clustering, and more [9]. There are a large number of widel...
In the context of modern agricultural intelligence, smart picking is becoming a crucial method for enhancing production efficiency. This paper proposes a tomato detection and localization system that integrates the YOLOv5 deep learning algorithm with the SGBM algorithm to improve detection accuracy and th...