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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...

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); ...

In this work, we revisit the global average pooling layer proposed in [13], and shed light on how it explicitly enables the convolutional neural network (CNN) to have remarkable localization ability despite being trained...

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...

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: 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 ...

Materias / palabras clave: Cluster analysis; Computer science; Correlation clustering; Consensus clustering; CURE data clustering algorithm; Fuzzy clustering; Single-linkage clustering; Conceptual clustering; Artificial intelligence; Clustering hi...

UAV (Unmanned Airborne Vehicle) high resolution digital image acquisition systems based on small format cameras provide a versatile alternative to the solution of environmental monitoring and remote sensing problems. Thr...

Segmentation is often a critical step in image analysis. Microscope image components show great variability of shapes, sizes, intensities and textures. An inaccurate segmentation conditions the ulterior quantification a...

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...

A tandem repeat in DNA is two or more contiguous, approximate copies of a pattern of nucleotides. Tandem repeats have been shown to cause human disease, may play a variety of regulatory and evolutionary roles and are imp...

Materias / palabras clave: computer vision, object recognition, image understanding, feature extraction, artificial intelligence, pattern recognition; Medicine: Medicine (General): Computer applications to medicine. Medical informatics; Science: M...