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Materias / palabras clave: Artificial intelligence; Pattern recognition (psychology); Clutter; Affine transformation; Computer science; Cognitive neuroscience of visual object recognition; Computer vision; Invariant (physics); Hough transform; 3D ...

Materias / palabras clave: Robustness (evolution); Mathematics; Artificial intelligence; Computer science; Algorithm; Machine learning; Kernel (algebra); Decision tree; Tree (set theory); Pattern recognition (psychology); Mathematical analysis; Ch...

State-of-the-art object detection networks depend on region proposal algorithms to hypothesize object locations. Advances like SPPnet [1] and Fast R-CNN [2] have reduced the running time of these detection networks, expo...

The highest accuracy object detectors to date are based on a two-stage approach popularized by R-CNN, where a classifier is applied to a sparse set of candidate object locations. In contrast, one-stage detectors that are...

Materias / palabras clave: Computer science; Suite; Neuroimaging; Software; Variety (cybernetics); Open source; Software suite; Human brain; Artificial intelligence; Software package; Pattern recognition (psychology); Neuroscience

Convolutional networks are powerful visual models that yield hierarchies of features. We show that convolutional networks by themselves, trained end-to-end, pixels-to-pixels, improve on the previous best result in semant...

Materias / palabras clave: Classifier (UML); Gene; Computer science; Feature selection; Redundancy (engineering); Gene selection; Support vector machine; Computational biology; sort; Artificial intelligence; Pattern recognition (psychology); Data ...

We propose a deep learning method for single image super-resolution (SR). Our method directly learns an end-to-end mapping between the low/high-resolution images. The mapping is represented as a deep convolutional neural...

Materias / palabras clave: Independent component analysis; Principal component analysis; Representation (politics); Computer science; Algorithm; Gaussian; Artificial intelligence; Projection (relational algebra); Pattern recognition (psychology); ...

We propose a simple, yet effective approach for spatiotemporal feature learning using deep 3-dimensional convolutional networks (3D ConvNets) trained on a large scale supervised video dataset. Our findings are three-fold...

We propose a novel approach for solving the perceptual grouping problem in vision. Rather than focusing on local features and their consistencies in the image data, our approach aims at extracting the global impression o...

We describe an object detection system based on mixtures of multiscale deformable part models. Our system is able to represent highly variable object classes and achieves state-of-the-art results in the PASCAL object det...

The way that information propagates in neural networks is of great importance. In this paper, we propose Path Aggregation Network (PANet) aiming at boosting information flow in proposal-based instance segmentation framew...

Materias / palabras clave: Computer science; Artificial intelligence; Convolutional neural network; Image (mathematics); Pixel; Perception; Transformation (genetics); Ground truth; Transfer (computing); Computer vision; Pattern recognition (psycho...

Point cloud is an important type of geometric data structure. Due to its irregular format, most researchers transform such data to regular 3D voxel grids or collections of images. This, however, renders data unnecessaril...

Introduction * Properties of Population Principal Components * Properties of Sample Principal Components * Interpreting Principal Components: Examples * Graphical Representation of Data Using Principal Components * Choos...

Materias / palabras clave: Artificial intelligence; Computer science; Face detection; AdaBoost; Pattern recognition (psychology); Object-class detection; Classifier (UML); Computer vision; Detector; Face (sociological concept); Facial recognition ...

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...

Materias / palabras clave: Pascal (unit); Benchmark (surveying); Artificial intelligence; Computer science; Object detection; Cognitive neuroscience of visual object recognition; Machine learning; Visual inspection; Context (archaeology); Object (...

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...

Materias / palabras clave: Voxel; Artificial intelligence; Voxel-based morphometry; Segmentation; Pattern recognition (psychology); Smoothing; Computer science; Gray (unit); Artifact (error); Gaussian; Parametric statistics; Market segmentation

Materias / palabras clave: Neuroscience; Segmentation; Artificial intelligence; Psychology; Pattern recognition (psychology); Computer science; Communication

Materias / palabras clave: Feature selection; Artificial intelligence; Selection (genetic algorithm); Computer science; Feature (linguistics); Pattern recognition (psychology); Machine learning; Linguistics; Philosophy

The explosion of image data on the Internet has the potential to foster more sophisticated and robust models and algorithms to index, retrieve, organize and interact with images and multimedia data. But exactly how such ...