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Materias / palabras clave: Computer science; Segmentation; Encoder; Artificial intelligence; Image segmentation; Feature (linguistics); Deep learning; Computer vision; Pattern recognition (psychology); Image (mathematics); Operating system; Lingui...

During the late 1990s, Huang introduced the algorithm called Empirical Mode Decomposition, which is widely used today to recursively decompose a signal into different modes of unknown but separate spectral bands. EMD is ...

We present Momentum Contrast (MoCo) for unsupervised visual representation learning. From a perspective on contrastive learning as dictionary look-up, we build a dynamic dictionary with a queue and a moving-averaged enco...

Materias / palabras clave: Computer science; The Internet; Vision; Telecommunications; Identification (biology); Paradigm shift; Data science; Wireless sensor network; Internet of Things; World Wide Web; Computer security; Computer network

Both convolutional and recurrent operations are building blocks that process one local neighborhood at a time. In this paper, we present non-local operations as a generic family of building blocks for capturing long-rang...

Computer vision applications have come to rely increasingly on superpixels in recent years, but it is not always clear what constitutes a good superpixel algorithm. In an effort to understand the benefits and drawbacks o...

Many underlying relationships among data in several areas of science and engineering, e.g., computer vision, molecular chemistry, molecular biology, pattern recognition, and data mining, can be represented in terms of gr...

Papers from the 2006 flagship meeting on neural computation, with contributions from physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The annual Neural Information Processing Systems (...

This is the first volume of the proposed many-sectioned "Handbook" in which the American Physiological Society intends to present comprehensively the entire field of physiology. The scope and depth of the work may be est...