This paper presents a traffic sign recognition algorithm for velocity signs, based on Linear Discriminant Analysis that performs dimensionality reduction and it improves class separability. The tests were perfo
Instance-based classifiers, such as k-NN, can overcome the challenge of “linearly inseparable” in malicious URLs detection. k-NN does not pursuit linear separability and only uses the labels of the surrounding points. But unlike SVM, which can learn a vector that rescales the original feature...
A modification of the softmax loss function, which is called Angular softmax (Zhao, Xu, & Cheng, 2019), was recently proposed as an explicit regularization technique, trying to increase the inter-class separability by distancing between class centers. Although this method, theoretically, leads to...
This paper presents a traffic sign recognition algorithm for velocity signs, based on Linear Discriminant Analysis that performs dimensionality reduction and it improves class separability. The tests were performed on the German Traffic Sign Recognition Benchmark, using a Multi-Layer Perceptron as a ...
This paper presents a traffic sign recognition algorithm for velocity signs, based on Linear Discriminant Analysis that performs dimensionality reduction and it improves class separability. The tests were performed on the German Traffic Sign Recognition Benchmark, using a Multi-Layer Perceptron as a ...
Clearly, linear-separability in H yields a quadratic separation in X, since we have a1z1+a2z2+a3z3+a4=a1⋅x12+a2⋅x1x2+a3⋅x22+a4⩾0. It is obvious that ϕ plays a crucial role in the feature enrichment process; for example, in this case linear separability is converted ...
However, a recent study in [19] has strongly indicated the existence of linear separability for this classification task when utilizing mathematical transformations of meteorological data. Therefore, linear classifiers seem to provide the high accuracy and robustness that are key properties together with ...
Historically, we have to mention that this type of lattice-valued equality was first introduced by Fourman and Scott [17] for investigations in logic and set theory and later by Höhle [17,18,19,20] in the theoretical development of fuzziness; this framework also contained a separability con...
The separability of data in a low-dimensional space can be used to determine whether the data can be separated in a high-dimensional space. We displayed t-SNE visualizations on five randomly selected classes of the VISOB dataset since it had a higher sample size per class than the other ...