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In this paper we present two basic modules whithin the designed scheme for retrieving images of a database from the object colour and shape in the scenes. On the one hand, we desing a new method to detect edges in colour...

Skeletal age assessment is one of the important applications of hand radiography in the area of pediatric radiology. Features analysis of the carpal bones can reveal the important information for skeletal age assessment....

Feature pyramids are a basic component in recognition systems for detecting objects at different scales. But pyramid representations have been avoided in recent object detectors that are based on deep convolutional netwo...

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...

An object recognition system has been developed that uses a new class of local image features. The features are invariant to image scaling, translation, and rotation, and partially invariant to illumination changes and a...

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 ...

We consider the problem of automatically recognizing human faces from frontal views with varying expression and illumination, as well as occlusion and disguise. We cast the recognition problem as one of classifying among...

We present the automated techniques we have developed for new software that optimally detects, deblends, measures and classifies sources from astronomical images: SExtractor (Source Extractor ). We show that a very relia...

Feature matching is at the base of many computer vision problems, such as object recognition or structure from motion. Current methods rely on costly descriptors for detection and matching. In this paper, we propose a ve...

Existing deep convolutional neural networks (CNNs) require a fixed-size (e.g., 224 × 224) input image. This requirement is "artificial" and may reduce the recognition accuracy for the images or sub-images of an arbitrar...

Abstract This book provides the first comprehensive treatment of feed-forward neural networks from the perspective of statistical pattern recognition. After introducing the basic concepts of pattern recognition, the book...

This document provides some basic guidance to start working with the EPOC Emotiv neuroheadset device and describes how to use it to perform basic Brain-Computer Interface (BCI) research. A brief tutorial on how to set up...

In recent years there has been a growing interest in the study of sparse representation of signals. Using an overcomplete dictionary that contains prototype signal-atoms, signals are described by sparse linear combinatio...

Multiscale feature extraction from the visual environment in an active vision system Y.Machrouh 1, J.-S.Liénard 1, P.Tarroux 1, 2 Abstract. This paper presents a visual architecture able to identify salient regions in a...