[PDF] Top 20 Learning discriminative features for face recognition
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Learning discriminative features for face recognition
... The previous equivalence suggests the possibility of using standard decision tree in- duction algorithms in place of a fixed tree to learn discriminative LBP-like descriptors from training data. We call this ... See full document
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Dealing with inaccurate face detection for automatic gender recognition with partially occluded faces
... since recognition rates reached by the LCH are very similar to those achieve using the ...dependent features were ...the recognition rate goes up until ...individual features were considered ... See full document
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Face recognition using adaptive dictionaries and sparse fingerprint classification algorithm
... proposed for dealing with occlusion and ...the learning of the dictionary. In Qiu et al. (2014), a discriminative and generative dictionary is learned based on the prin- ciple of information ... See full document
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Deep Learning for Object Recognition in picking tasks
... the features of the provided object followed by feature matching in the given ...time for real time detection. There have been solution for them as well such as the ORB (Rublee et ...keypoints ... See full document
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https://cdn-shop.adafruit.com/product-files/4095/4095_Getting_Started_Guide.md_at_master____espressif_esp-who____GitHub.pdf
... ESP-EYE is an ESP32-based development board that integrates a digital microphone, an 8 MB PSRAM and a 4 MB flash, while also providing an external 2-Megapixel camera. These features make the board ideal for ... See full document
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Exploring differences between phonetic classes in Sleep Apnoea Syndrome Patients using automatic speech processing techniques
... speech recognition system is the process involved in extracting a set of acoustic features from the speech signal, so that it provides an efficient representation of speech without losing ... See full document
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Automatic Emotion Recognition From Multimodal Information Fusion Using Deep Learning Approaches
... systems. For doing so, emotions have been characterized by specific kind of data including audio, facial expressions, physiological signals, among ...more learning patterns to perform emotion ...Deep ... See full document
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Reconocimiento Automático de Actividades Humanas Basado en el Análisis de Secuencias de Imágenes
... method for many face recognition systems ...alternative for the considered pattern recognition ...supervised learning technique used for both classification and regression ... See full document
190
Do we need an open face recognition search engine?
... a face recognition capability: the gamers face and facial expressions are reproduced by their character inside the ...also face biometrics. The gaming platform used a face ... See full document
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Measuring external face appearance for face classification
... external features are the regions of the hair, forehead, both laterals, ears, jaw line and ...Traditionally, face recognition algorithms have used only the internal information of face images ... See full document
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The implementation of collaborative study groups for promoting pronunciation learning
... collaborative learning elements such as positive interdependence, individual accountability, face-to-face interaction and group ...regarding features of the International Phonetic Alphabet ... See full document
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Analysis and implementation of deep learning algorithms for face to face translation based on audio-visual representations
... exponent for the magnitude Mel-spectrogram (in this case 2 for power), the lowest and highest frequency and the number of Mel bands to generate, ...appear. For the purpose of the spectrogram display, ... See full document
196
Multitask learning : An application to incremental face recognition
... different face databases: the Face Recognition Grand Challenge (Phillips et ...AR Face database (Martinez and Benavente, ...500 features from each data set, and then a discriminant ... See full document
6
Advanced face and gesture recognition for visual HMI
... aspect ratio of the bounding box that encloses a hand region can dramatically change, and subsequently the derived feature descriptor. This makes the learning process of a classier very complex, since very ... See full document
165
A combination of spatiotemporal ica and euclidean features for face recognition
... Face recognition is one of the most successful applications of image processing and analysis, and it has become one of the major topics in the research areas of machine vision and pattern recognition ... See full document
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TítuloE learning and Face to Face Mixed Methodology: Evaluating effectiveness of e learning and perceived satisfaction for a microeconomic course using the Moodle Platform
... Qualification is obtained automatically, by means of the parameters specified at the time of preparation of the test. The system, as we have said, allows evaluating in different ways each of the questions, and also to ... See full document
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Neural processing of emotional facial and semantic expressions in euthymic bipolar disorder (BD) and its association with theory of mind (ToM)
... of face processing ...component for each condition were estimated using the standardized low-resolution brain electromagnetic tomography algorithm (sLORETA ...constrained for location. Selected ... See full document
12
Isolated spanish digit recognition based on audio-visual features
... speech recognition techniques based on audio features is degraded in noisy ...visual features related to mouth movements into the recogni- tion process improves the performance of the ...speech ... See full document
10
Parallelizing algorithms in ada on clementina II . Face recognition system
... In the Laboratory of Research and Development on Computer Science of the National University of La Plata, a face recognition system has been developed. This article describes a series of testings based on ... See full document
10
How Blended Learning Reduce Underachievement in Higher Education: An Experience in Teaching Computer Sciences.
... The view taken here is that e-learning achieves a better score than face-to-face tuition, basically because e-learning is individ- ualized (the student learns through self-study and sel[r] ... See full document
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