Results 41 to 50 of about 815,001 (281)

Response : Computing with Neural Networks [PDF]

Science, 1987
Response: The intellectual thrust of our article (1) was to show the neurobiologist how a conceptual framework and methodology could be used to understand how a class of model neural circuits solve specific computational problems. In addition, we used examples of model circuit computation to illustrate the general problems neurobiologists face in ...
J J, Hopfield, D W, Tank
openaire   +2 more sources

Probabilistic classification of quality of service in wireless computer networks

ICT Express, 2019
There is an increasing reliance on wireless computer networks for communicating various types of time sensitive applications such as voice over internet protocol (VoIP). Quality of service (QoS) can play an important role in wireless computer networks as
Abdussalam Salama, Reza Saatchi
doaj   +1 more source

Subitizing with Variational Autoencoders

, 2018
Numerosity, the number of objects in a set, is a basic property of a given visual scene. Many animals develop the perceptual ability to subitize: the near-instantaneous identification of the numerosity in small sets of visual items.
A Nieder, A Nieder, BM Harvey, BR Jansen, C Arteta, D Burr, E Walach, EL Kaufman, G Lakoff, G Lemaître, H Davis, I Goodfellow, I Stoianov, J Zhang, L Feigenson, M Piazza, M Poncet, M-M Cheng, MC Franka, Olga Russakovsky, P Viswanathan, S Dehaene, T-Y Lin, WS Jevons, Y Hu, Y LeCun   +25 more
core   +1 more source

Modulation of feedback-related negativity by objective and subjective response correctness

Scientific Reports
Monitoring actions and outcomes is essential for flexible adaptation to environmental demands. Information about errors is important regardless of whether it is internally generated or externally signaled.
Yasuhisa Maruyama, Keita Aoyama, Osamu Fukayama   +2 more
doaj   +1 more source

A primer on deep learning and convolutional neural networks for clinicians

Insights into Imaging, 2021
Deep learning is nowadays at the forefront of artificial intelligence. More precisely, the use of convolutional neural networks has drastically improved the learning capabilities of computer vision applications, being able to directly consider raw data ...
Lara Lloret Iglesias, Pablo Sanz Bellón, Amaia Pérez del Barrio, Pablo Menéndez Fernández-Miranda, David Rodríguez González, José A. Vega, Andrés A. González Mandly, José A. Parra Blanco   +7 more
doaj   +1 more source

Neural Networks Architecture Evaluation in a Quantum Computer

, 2017
In this work, we propose a quantum algorithm to evaluate neural networks architectures named Quantum Neural Network Architecture Evaluation (QNNAE). The proposed algorithm is based on a quantum associative memory and the learning algorithm for artificial
da Silva, Adenilton José, de Oliveira, Rodolfo Luan F.   +1 more
core   +1 more source

Integrating evolutionary computation with neural networks [PDF]

Proceedings Electronic Technology Directions to the Year 2000, 2002
There is a tremendous interest in the development of the evolutionary computation techniques as they are well suited to deal with optimization of functions containing a large number of variables. This paper presents a brief review of evolutionary computing techniques.
Vonk, E., Jain, L.C., Veelenturf, L.P.J., Hibbs, R.A.   +3 more
openaire   +1 more source

Clinical Insights Into Hypercalcemia of Malignancy in Childhood

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Hypercalcemia of malignancy (HCM) is a rare but life‐threatening metabolic emergency in children that occurs in less than 1% of pediatric cancer cases, with a reported incidence ranging from 0.4% to 1.0% across different studies. While it is observed in 10%–20% of adult malignancies, pediatric HCM remains relatively uncommon.
Hüseyin Anıl Korkmaz
wiley   +1 more source

A decade of adversarial examples: a survey on the nature and understanding of neural network non-robustness

Компьютерная оптика
Adversarial examples, in the context of computer vision, are inputs deliberately crafted to deceive or mislead artificial neural networks. These examples exploit vulnerabilities in neural networks, resulting in minimal alterations to the original input ...
A.V. Trusov, E.E. Limonova, V.V. Arlazarov   +2 more
doaj   +1 more source

Anti-periodic behavior for quaternion-valued delayed cellular neural networks

Advances in Difference Equations, 2021
In this manuscript, quaternion-valued delayed cellular neural networks are studied. Applying the continuation theorem of coincidence degree theory, inequality techniques and a Lyapunov function approach, a new sufficient condition that guarantees the ...
Zhenhua Duan, Changjin Xu
doaj   +1 more source