ALAMEH M.

Embedding machine learning methods into the data decoding units may enable the extraction of complex information making the tactile sensing systems intelligent. This paper presents and compares the implementations of a convolutional neural network model for tactile data decoding on various hardware platforms. Experimental results show...

Tactile data processing and analysis is still essentially an open challenge. In this framework, we demonstrate a method to achieve touch modality classification using pre-trained convolutional neural networks (CNNs). The 3D tensorial tactile data generated by real human interactions on an electronic skin (E-Skin) are transformed into 2D images....

Machine and deep learning algorithms are currently employed for many applications such as computer vision, speech recognition and portable/wearable electronics. Regrettably, machine learning algorithms have high complexity adding more challenges for the implementation of such algorithms on embedded hardware platforms. This paper aims to present...

Recurrent Neural Networks (RNNs) are mainly designed to deal with sequence prediction problems and they show their effectiveness in processing data originally represented as time series. This paper investigates the time series characteristics of RNNs to classify touch modalities represented as spatio temporal 3D tensor data. Different...

This chapter presents a survey of the existing algorithms and tasks applied for tactile data processing. The presented algorithms and tasks include machine learning, deep learning, feature extraction, and dimensionality reduction. Moreover, this chapter provides guidelines for selecting appropriate hardware platforms for the algorithm's...

Context awareness was introduced recently in several fields in quotidian human activities. Among context aware applications, health care systems are the most important ones. Such applications, in order to perceive the context, rely on sensors which may be physical or virtual. However, these applications lack of standardization in handling the...

Human-object interaction is of great relevance for robots to operate in human environments. However, state-of-the-art robotic hands are far from replicating humans skills. It is, therefore, essential to study how humans use their hands to develop similar robotic capabilities. This article presents a deep dive into hand-object interaction and...