AIMC Topic: Hand

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Light-Weight Deep Learning Techniques with Advanced Processing for Real-Time Hand Gesture Recognition.

Sensors (Basel, Switzerland)
In the discipline of hand gesture and dynamic sign language recognition, deep learning approaches with high computational complexity and a wide range of parameters have been an extremely remarkable success. However, the implementation of sign languag...

Exploiting domain transformation and deep learning for hand gesture recognition using a low-cost dataglove.

Scientific reports
Hand gesture recognition is one of the most widely explored areas under the human-computer interaction domain. Although various modalities of hand gesture recognition have been explored in the last three decades, in recent years, due to the availabil...

Hand Gesture Recognition Using EMG-IMU Signals and Deep Q-Networks.

Sensors (Basel, Switzerland)
Hand gesture recognition systems (HGR) based on electromyography signals (EMGs) and inertial measurement unit signals (IMUs) have been studied for different applications in recent years. Most commonly, cutting-edge HGR methods are based on supervised...

GMLM-CNN: A Hybrid Solution to SWIR-VIS Face Verification with Limited Imagery.

Sensors (Basel, Switzerland)
Cross-spectral face verification between short-wave infrared (SWIR) and visible light (VIS) face images poses a challenge, which is motivated by various real-world applications such as surveillance at night time or in harsh environments. This paper p...

Ultrasound Probe and Hand-Eye Calibrations for Robot-Assisted Needle Biopsy.

Sensors (Basel, Switzerland)
In robot-assisted ultrasound-guided needle biopsy, it is essential to conduct calibration of the ultrasound probe and to perform hand-eye calibration of the robot in order to establish a link between intra-operatively acquired ultrasound images and r...

EMG-driven shared human-robot compliant control for in-hand object manipulation in hand prostheses.

Journal of neural engineering
. The limited functionality of hand prostheses remains one of the main reasons behind the lack of its wide adoption by amputees. Indeed, while commercial prostheses can perform a reasonable number of grasps, they are often inadequate for manipulating...

Design and Gesture Optimization of a Soft-Rigid Robotic Hand for Adaptive Grasping.

Soft robotics
Soft robotic hands are inherently safer and more compliant in robot-environment interaction than rigid manipulators, but their flexibility and versatility still need improving. In this article, a gesture adaptive soft-rigid robotic hand is proposed. ...

NeuroGrasp: Real-Time EEG Classification of High-Level Motor Imagery Tasks Using a Dual-Stage Deep Learning Framework.

IEEE transactions on cybernetics
Brain-computer interfaces (BCIs) have been widely employed to identify and estimate a user's intention to trigger a robotic device by decoding motor imagery (MI) from an electroencephalogram (EEG). However, developing a BCI system driven by MI relate...

Co-optimization of robotic design and skill inspired by human hand evolution.

Bioinspiration & biomimetics
During evolution of the human hand, evolutionary morphology has been closely related to behavior in complicated environments. Numerous researchers have revealed that learned skills have affected hand evolution. Inspired by this phenomenon, a co-optim...

HandVoxNet++: 3D Hand Shape and Pose Estimation Using Voxel-Based Neural Networks.

IEEE transactions on pattern analysis and machine intelligence
3D hand shape and pose estimation from a single depth map is a new and challenging computer vision problem with many applications. Existing methods addressing it directly regress hand meshes via 2D convolutional neural networks, which leads to artifa...