A review of tactile information: Perception and action through touch
Tactile sensing is a key sensor modality for robots interacting with their surroundings. These
sensors provide a rich and diverse set of data signals that contain detailed information …
sensors provide a rich and diverse set of data signals that contain detailed information …
Deep learning in robotics: Survey on model structures and training strategies
The ever-increasing complexity of robot applications induces the need for methods to
approach problems with no (viable) analytical solution. Deep learning (DL) provides a set of …
approach problems with no (viable) analytical solution. Deep learning (DL) provides a set of …
Self-supervised visual terrain classification from unsupervised acoustic feature learning
Mobile robots operating in unknown urban environments encounter a wide range of
complex terrains to which they must adapt their planned trajectory for safe and efficient …
complex terrains to which they must adapt their planned trajectory for safe and efficient …
Sound source localization in a multipath environment using convolutional neural networks
The propagation of sound in a shallow water environment is characterized by boundary
reflections from the sea surface and sea floor. These reflections result in multiple (indirect) …
reflections from the sea surface and sea floor. These reflections result in multiple (indirect) …
A deep convolution neural network method for land cover map**: A case study of Qinhuangdao, China
Y Hu, Q Zhang, Y Zhang, H Yan - Remote Sensing, 2018 - mdpi.com
Land cover and its dynamic information is the basis for characterizing surface conditions,
supporting land resource management and optimization, and assessing the impacts of …
supporting land resource management and optimization, and assessing the impacts of …
Deep recurrent neural networks for audio classification in construction sites
In this paper, we propose a Deep Recurrent Neural Network (DRNN) approach based on
Long-Short Term Memory (LSTM) units for the classification of audio signals recorded in …
Long-Short Term Memory (LSTM) units for the classification of audio signals recorded in …
Feature learning for fault detection in high-dimensional condition monitoring signals
Complex industrial systems are continuously monitored by a large number of
heterogeneous sensors. The diversity of their operating conditions and the possible fault …
heterogeneous sensors. The diversity of their operating conditions and the possible fault …
Deep spatiotemporal models for robust proprioceptive terrain classification
Terrain classification is a critical component of any autonomous mobile robot system
operating in unknown real-world environments. Over the years, several proprioceptive …
operating in unknown real-world environments. Over the years, several proprioceptive …
Flatten-T Swish: a thresholded ReLU-Swish-like activation function for deep learning
Activation functions are essential for deep learning methods to learn and perform complex
tasks such as image classification. Rectified Linear Unit (ReLU) has been widely used and …
tasks such as image classification. Rectified Linear Unit (ReLU) has been widely used and …
Convolutional neural networks for passive monitoring of a shallow water environment using a single sensor
A cost effective approach to remote monitoring of protected areas such as marine reserves
and restricted naval waters is to use passive sonar to detect, classify, localize, and track …
and restricted naval waters is to use passive sonar to detect, classify, localize, and track …