This paper proposes a method to estimate road boundaries in different environments with deep learning-based semantic segmentation, and without any predefined road markings.
The machine learning (ML) algorithms that have been used here are Logistic Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), and Artificial Neural Network (ANN).
This paper presents a method of capturing objects appearances from its environment and it also describes how to recognize unknown appearances creating an eigenspace.
This paper presents two different evolutionary systems - Evolutionary Programming Network (EPNet) and Novel Evolutions Strategy (NES) Algorithm.
Fuzzy systems may be considered as knowledge-based systems that incorporates human knowledge into their knowledge base through fuzzy rules and fuzzy membership functions.
Solving large traveling salesman problem (TSP) in an efficient way is a challenging area for the researchers of computer science.
In the both above hybrid evolutionary methods, uniform adaptation (UA) techniques are used to adapt relaxation factor.
Recently, hybridization of evolutionary algorithm with classical Gauss-Seidel based Successive Over Relaxation (SOR) method has successfully been used to solve large number of linear equations; where a uniform adaptation (UA) technique of relaxation factor is used.
Also the proposed modified algorithms require less amount of computational time in comparison to the corresponding existing hybrid algorithms.
Single document summarization generates summary by extracting the representative sentences from the document.
Thus this work illustrates how the choice of aggregation operators is intended to mimic human decision making and can be selected and adjusted to fit empirical data, a series of test cases.
In DNESA, the server distributes the total computation load to all associate clients and simulation results show that the time for solving large problems is much less than sequential EAs.
Extracting minutiae from fingerprint images is one of the most important steps in automatic fingerprint identification system.
In this paper, a new hybrid algorithm is proposed in which uniform adaptive evolutionary computation techniques and classical Jacobi based SR technique are used instead of classical Gauss-Seidel based SR technique.
The linguistic variables are defined for both T and P and then these variables are implemented in our laboratory to verify the proposed trust model.
Cryptography and Security