Traditional methods of computer vision and machine learning cannot match human performance on tasks such as the recognition of handwritten digits or traffic signs. Our biologically plausible, wide and deep artificial neural network architectures can. Small (often minimal) recepti…
Most current speech recognition systems use hidden Markov models (HMMs) to deal with the temporal variability of speech and Gaussian mixture models (GMMs) to determine how well each state of each HMM fits a frame or a short window of frames of coefficients that represents the aco…
This article presents an overview of some of the most used optimizers while training a neural network.
This article summarizes anatomical, neurophysiological, pharmacological, and brain imaging studies in humans and animals that have provided insights into the neural circuitry and neurotransmitter mechanisms controlling the lower urinary tract. The functions of the lower urinary t…
During micturition, according to the concept of Blok, Holstege, and colleagues ([1997] Neurosci. Lett. 233:109-112), the pontine micturition center (PMC) elicits bladder contraction by way of direct excitation of the parasympathetic bladder motoneurons. At the same time, the PMC…
Micturition is a spino-bulbo-spinal reflex. The bulbospinal part of this reflex is formed by the projections from the M-region, also called the pontine micturition center or Barrington's nucleus, to the preganglionic parasympathetic motoneurons in the sacral cord innervating the…
A computer Go program based on deep neural networks defeats a human professional player to achieve one of the grand challenges of artificial intelligence.
In recent years, deep artificial neural networks (including recurrent ones) have won numerous contests in pattern recognition and machine learning. This historical survey compactly summarizes relevant work, much of it from the previous millennium. Shallow and Deep Learners are di…
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TinEye is an image search and recognition company. We are experts in computer vision, pattern recognition, neural networks, and machine learning.
From its institution as the Neural Networks Council in the early 1990s, the IEEE Computational Intelligence Society has rapidly grown into a robust community wi
подбор материалов на темы непосредственно связанные с искусственным интеллектом: генетические алгоритмы, нейронные сети, экспертные системы, логика предикатов, нечеткая логика и др., практическое применение данных подходов к решению комплексных задач реального масштаба, скачать д…
Hierarchical neural networks for object recognition have a long history. In recent years, novel methods for incrementally learning a hierarchy of features from unlabeled inputs were proposed as good starting point for supervised training. These deep learning methods—together with…
Since the beginnings of computer technology, researchers have speculated about the possibility of building smart machines that could compete with human intelligence. Given the current pace of advances in artificial intelligence and neural computing, such an evolution seems to be…
Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort<sup>1-4</sup>, the structures of around 100,000 unique proteins have been determined<sup>5</sup>, but this repre…
Define neural. neural synonyms, neural pronunciation, neural translation, English dictionary definition of neural. adj. 1. Of or relating to a nerve or the nervous system.
Neural codes form an algebraic framework to study the nervous system, and understanding neural codes is a key goal of mathematical neuroscience. Neural rings and ideals are the tools connecting neuroscience and commutative algebra. In this article, w...