Titlebook: Artificial Intelligence and Soft Computing; 18th International C Leszek Rutkowski,Rafa? Scherer,Jacek M. Zurada Conference proceedings 2019

羽毛長成

Robust Training of Radial Basis Function Neural Networksh searches sequentially for the most reliable subset of observations and finally performs outlier deletion. The novel approach is investigated in numerical experiments and is also applied to robustify a multilayer perceptron. The results on data containing outliers reveal the improved performance compared to conventional approaches.

不斷的變動

連累

Microscopic Sample Segmentation by Fully Convolutional Network for Parasite Detectionsparency look similar, and some of parasites eggs might be unintentionally omitted. The presented method based on fully convolutional network allows processing the entire space of the sample and assigning a class to each pixel of the image. Our model was trained to classify parasite eggs and distinguish them from adjacent or overlapped pollution.