Results 131 to 140 of about 1,702,697 (182)

Trait anxiety is associated with reduced reward-related replay at rest. [PDF]

Nat Commun
Yu Q, Luo YJ, Dolan R, Ou J, Huang C, Wang H, Xiao Z, Nour M, Liu Y.   +8 more
europepmc   +1 more source

Benchmarking quantum versions of the kNN algorithm with a metric based on amplitude-encoded features. [PDF]

Sci Rep
Guerrero-Estrada AY, Quezada LF, Sun GH.
europepmc   +1 more source

A hybrid object detection approach for visually impaired persons using pigeon-inspired optimization and deep learning models. [PDF]

Sci Rep
Alashjaee AM, AlEisa HN, Darem AA, Marzouk R.   +3 more
europepmc   +1 more source

C-parameter version of robust bounded one-class support vector classification. [PDF]

Sci Rep
Ye J, Yang Z, Hu Y, Zhang Z.
europepmc   +1 more source

Digital accessibility in the era of artificial intelligence-Bibliometric analysis and systematic review. [PDF]

Front Artif Intell
Chemnad K, Othman A.
europepmc   +1 more source

Fast and exact fixed-radius neighbor search based on sorting. [PDF]

PeerJ Comput Sci
Chen X, Güttel S.
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Adversarial Attacks in Banknote Recognition Systems

2021 4th International Conference on Data Storage and Data Engineering, 2021
Numerous computer vision algorithms have been designed to help detect the values of the paper banknotes for blind and visually impaired individuals.
Hangyu Liu, Hao Cai
semanticscholar   +2 more sources

Overview of Deep Learning Models for Banknote Recognition

2023 17th International Conference on Electronics Computer and Computation (ICECCO), 2023
This paper offers a comparative analysis of various deep learning models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Deep Belief Networks (DBNs), applied to the task of banknote recognition.
Ualikhan Sadyk, Cemil Turan, Rashid Baimukashev   +2 more
semanticscholar   +2 more sources

Yemeni Banknote Recognition Model based on Convolution Neural Networks

2021 1st International Conference on Emerging Smart Technologies and Applications (eSmarTA), 2021
Differentiating between paper currencies with different designs is a challenging task for visually impaired individuals and automated banking machines. Safe and accurate paper currency recognition systems are highly required, because of the wide use of ...
Ahmed Y. A. Saeed, Abdulfattah Ba Alawi, A. Hassan   +2 more
semanticscholar   +2 more sources