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Predicting face attributes in the wild is challenging due to complex face variations. We propose a novel deep learning framework for attribute prediction in the wild. It cascades two CNNs, LNet and ANet, which are fine-t...

In modern face recognition, the conventional pipeline consists of four stages: detect => align => represent => classify. We revisit both the alignment step and the representation step by employing explicit 3D face modeli...

Recent work has shown that convolutional networks can be substantially deeper, more accurate, and efficient to train if they contain shorter connections between layers close to the input and those close to the output. In...

Previous work has shown that the difficulties in learning deep generative or discriminative models can be overcome by an initial unsupervised learning step that maps inputs to useful intermediate representations. We intr...

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...

Feature selection is an important problem for pattern classification systems. We study how to select good features according to the maximal statistical dependency criterion based on mutual information. Because of the dif...

We propose a deep convolutional neural network architecture codenamed Inception that achieves the new state of the art for classification and detection in the ImageNet Large-Scale Visual Recognition Challenge 2014 (ILSVR...

We study the question of feature sets for robust visual object recognition; adopting linear SVM based human detection as a test case. After reviewing existing edge and gradient based descriptors, we show experimentally t...

This paper presents a robust eye detection algorithm for gray intensity images. The idea of our method is to combine the respective advantages of two existing techniques, feature based method and template based method, a...

Este proyecto presenta el análisis de la factibilidad para el desarrollo de un prototipo que calcule en tiempo-real la humedad de la yerba mate a la salida del sapecador. Para lo cual se utilizarán técnicas de intelig...

This work develops a system to visualize the information for radar systems interfaces. It is a flexible, portable software system that allows to be used for radars that have different technologies and that is able to be ...

The algorithmical architecture and structure is presented for the parallelization of image similarity analysis, based on obtaining multiple digital signatures for each image, in which each "signature" is composed by the ...

En los últimos tiempos, una de las áreas que despierta mayor interés y que ha tenido más auge dentro del amplio campo de la informática es la del procesamiento paralelo. El paralelismo invade no sólo las super-comp...

Este trabajo describe una línea de I/D y los resultados esperados de la misma. El objetivo principal es estudiar, desarrollar y evaluar métodos computacionales de reconocimiento estadístico de patrones en particular c...

La visión artificial por reconocimiento de patrones es un concepto que permite dar visión de mayor calidad, ver en tiempo real y seguir objetos. Dependiendo de su posición, orientación o tamaño, un objeto puede gene...

Subjects / keywords: Computer science; Deep learning; Artificial intelligence; Abstraction; Representation (politics); Layer (electronics); Object (grammar); Backpropagation; Convolutional neural network; Feature learning; Pattern recognitio...

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

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...

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

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

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

The rapid proliferation of unmanned aerial vehicles (UAVs) has created an urgent need for robust detection & identification systems to ensure airspace security and safety. However, the scarcity of large-scale, div...

Abstract The cyclic five-membered disulfide 1,2-dithiolane, known for its moderate reactivity and ease of preparation, holds significant promise as a recognition unit in probe design and drug development. However, potent...

IMPORTANCE: Limited information exists about the epidemiology, recognition, management, and outcomes of patients with the acute respiratory distress syndrome (ARDS). OBJECTIVES: To evaluate intensive care unit (ICU) inci...