|
|
|
|
|
Chuanyun Xu, Hang Wang, Yang Zhang, Zheng Zhou and Gang Li
Few-shot learning refers to training a model with a few labeled data to effectively recognize unseen categories. Recently, numerous approaches have been suggested to improve the extraction of abundant feature information at hierarchical layers or multipl...
ver más
|
|
|
|
|
|
|
|
|
Károly Héberger
Background: The development and application of machine learning (ML) methods have become so fast that almost nobody can follow their developments in every detail. It is no wonder that numerous errors and inconsistencies in their usage have also spread wi...
ver más
|
|
|
|
|
|
|
|
|
Ahmed Alwakeel, Mohammed Alwakeel, Mohammad Hijji, Tausifa Jan Saleem and Syed Rameem Zahra
Image classification is one of the major data mining tasks in smart city applications. However, deploying classification models that have good generalization accuracy is highly crucial for reliable decision-making in such applications. One of the ways to...
ver más
|
|
|
|
|
|
|
|
|
Yuyang Hao, Kan He and Ying Zhang
In this paper, we establish an aggregate class distribution neural network (AGGNN) structure to determine whether an arbitrary two-qubit quantum state is steerable. Compared to the classification results obtained using a support vector machine (SVM) and ...
ver más
|
|
|
|
|
|
|
|
|
Yang Chen, Xikui Sun, Xiufeng Zhang, Peng Gu, Guoying Li, Shenglong Yang, Deyuan Fan, Chuancheng Liu and Xuesheng Liu
The impact risk evaluation for the strip filling of working faces has always been a research hotspot and a difficulty in the field of rock bursts. In this paper, the concept of the critical filling rate is first proposed, and the criterion for identifyin...
ver más
|
|
|
|