Titlebook: Artificial Intelligence and Soft Computing; 20th International C Leszek Rutkowski,Rafa? Scherer,Jacek M. Zurada Conference proceedings 2021

艦旗

Karlheinz Lohs,Peter Elstner,Ursula Stephanent of skin lesions asymmetry, along with various variations of the PH2 database. For the best CNN network, we achieved the following results: true positive rate for the asymmetry 92.31%, weighted accuracy 67.41%, F1 score 0.646 and Matthews correlation coefficient 0.533.

Condescending

著名

https://doi.org/10.1007/b138937 the corpus and attack the most important words in each sentence. The rating is global to the whole corpus and not to each specific data point. This method performs equal or better when compared to previous attack methods, and its running time is around 39 times faster than previous models.

半身雕像

時(shí)間等

Karlheinz Lohs,Peter Elstner,Ursula Stephaneled training images, minimizing the specialist’s annotation effort. The validation of our proposed methodology is done on a public breast lesion-related dataset and our results show considerable accuracy gains over the traditional supervised learning approach and reductions of up?to . in the labeled training sets.

有限

Graduated

fidelity

A Computer Vision Based Approach forDriver Distraction Recognition Using Deep Learning and Genetic A technique achieves an accuracy of 96.37%, surpassing the previously obtained 95.98%, and on the State Farm Driver Distraction Dataset, on which we attain an accuracy of 99.75%. The 6-Model Ensemble gave an inference time of 0.024?s as measured on our machine with Ubuntu 20.04(64-bit) and GPU as GeForce GTX 1080.

lanugo

hermetic