|
|
|
|
|
SeyedehRoksana Mirzaei, Hua Mao, Raid Rafi Omar Al-Nima and Wai Lok Woo
Explainable Artificial Intelligence (XAI) evaluation has grown significantly due to its extensive adoption, and the catastrophic consequence of misinterpreting sensitive data, especially in the medical field. However, the multidisciplinary nature of XAI ...
ver más
|
|
|
|
|
|
|
|
|
Thomas Parr, Karl Friston and Peter Zeidman
Bayesian inference typically focuses upon two issues. The first is estimating the parameters of some model from data, and the second is quantifying the evidence for alternative hypotheses?formulated as alternative models. This paper focuses upon a third ...
ver más
|
|
|
|
|
|
|
|
|
Suryakant Tyagi and Sándor Szénási
Machine learning and speech emotion recognition are rapidly evolving fields, significantly impacting human-centered computing. Machine learning enables computers to learn from data and make predictions, while speech emotion recognition allows computers t...
ver más
|
|
|
|
|
|
|
|
|
Javensius Sembiring, Rianto Adhy Sasongko, Eduardo I. Bastian, Bayu Aji Raditya and Rayhan Ekananto Limansubroto
This paper investigates the development of a deep learning-based flight control model for a tilt-rotor unmanned aerial vehicle, focusing on altitude, speed, and roll hold systems. Training data is gathered from the X-Plane flight simulator, employing a p...
ver más
|
|
|
|
|
|
|
|
|
Yugen Yi, Haoming Zhang, Ningyi Zhang, Wei Zhou, Xiaomei Huang, Gengsheng Xie and Caixia Zheng
As the feature dimension of data continues to expand, the task of selecting an optimal subset of features from a pool of limited labeled data and extensive unlabeled data becomes more and more challenging. In recent years, some semi-supervised feature se...
ver más
|
|
|
|