Data-driven approaches for non-invasive cuffless blood pressure monitoring
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A new learning strategy for object detection is presented. The proposed scheme forgoes the need to train a collection of detectors dedicated to homogeneous families of poses, and instead learns a single classifier that has the inherent ability to deform ba ...
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A common trend in machine learning and pattern classification research is the exploitation of massive amounts of information in order to achieve an increase in performance. In particular, learning from huge collections of data obtained from the web, and us ...
A common trend in machine learning and pattern classification research is the exploitation of massive amounts of information in order to achieve an increase in performance. In particular, learning from huge collections of data obtained from the web, and us ...
This paper presents realization and the laboratory tests of the Kohonen winner takes all (WTA) neural network (NN) realized on microcontrollers (μC) with the AVR and ARM CortexM3 cores. Both μCs have been placed on a single testing board especially designe ...
This paper completes the study presented in the accompanying paper, and demonstrates a numerical algorithm for parameter prediction from the piezocone test (CPTU) data. This part deals with a development of neural network (NN) models which are able to map ...
Extracting linear structures, such as blood vessels or dendrites, from images is crucial in many medical imagery applications, and many handcrafted features have been proposed to solve this problem. However, such features rely on assumptions that are never ...
This paper investigates the use of a hierarchy of Neural Networks for performing data driven feature extraction. Two different hierarchical structures based on long and short temporal context are considered. Features are tested on two different LVCSR syste ...
This paper investigates the use of a hierarchy of Neural Networks for performing data driven feature extraction. Two different hierarchical structures based on long and short temporal context are considered. Features are tested on two different LVCSR syste ...
We will explore dynamic perception following the visually guided grasping of several objects by a human-like autonomous robot. This competency serves for object categorization. Physical interaction with the hand-held object gives the neural network of the ...
In the framework of indoor mobile robotics, place recognition is a challenging task, where it is crucial that self-localization be enforced precisely, notwithstanding the changing conditions of illumination, objects being shifted around and/or people affec ...
