Object recognition algorithm based on optimized nonlinear activation function-global convolutional neural network

Traditional object recognition algorithms cannot meet the requirements of object recognition accuracy in the actual warehousing and logistics field. In recent years, the rapid development of the deep learning theory has provided a technical approach for solving the above problems, and a number of ob...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	The Visual computer Jg. 38; H. 2; S. 541 - 553
Hauptverfasser:	An, Feng-Ping, Liu, Jun-e, Bai, Lei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2022 Springer Nature B.V
Schlagworte:	Accuracy Algorithms Artificial Intelligence Artificial neural networks Classification Computer Graphics Computer Science Datasets Deep learning Feature maps Image Processing and Computer Vision Learning theory Machine learning Mathematical models Modelling Neural networks Object recognition Original Article Parameters Target recognition Deep learning Global convolutional neural network Object recognition Nonlinear activation function Object detection
ISSN:	0178-2789, 1432-2315
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!