Deep convolutional neural networks with ensemble learning and transfer learning for capacity estimation of lithium-ion batteries
It is often difficult for a machine learning model trained based on a small size of
charge/discharge cycling data to produce satisfactory accuracy in the capacity estimation of …
charge/discharge cycling data to produce satisfactory accuracy in the capacity estimation of …
Domain and writer adaptation of offline Arabic handwriting recognition using deep neural networks
SK Jemni, S Ammar, Y Kessentini - Neural Computing and Applications, 2022 - Springer
Abstract Arabic Handwritten Text Recognition (AHTR) based on deep learning approaches
remains a challenging problem due to the inevitable domain shift like the variability among …
remains a challenging problem due to the inevitable domain shift like the variability among …
Transfer learning for vehicle detection using two cameras with different focal lengths
This paper proposes a vehicle detection method using transfer learning for two cameras with
different focal lengths. A detected vehicle region in an image of one camera is transformed …
different focal lengths. A detected vehicle region in an image of one camera is transformed …
Learning to predict robot keypoints using artificially generated images
This work considers robot keypoint estimation on color images as a supervised machine
learning task. We propose the use of probabilistically created renderings to overcome the …
learning task. We propose the use of probabilistically created renderings to overcome the …
Optimizing keypoint-based single-shot camera-to-robot pose estimation through shape segmentation
J Lambrecht, P Grosenick… - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
We introduce an optimization method for recent approaches on keypoint-based pose
estimation of robotic manipulators utilizing monocular images. The method takes into …
estimation of robotic manipulators utilizing monocular images. The method takes into …
G-SAM: A Robust One-Shot Keypoint Detection Framework for PnP Based Robot Pose Estimation
Robot pose estimation plays a fundamental role in various applications involving service
and industrial robots. Among the methods used for robot pose estimation from a single …
and industrial robots. Among the methods used for robot pose estimation from a single …
Promoting transfer of robot neuro-motion-controllers by many-objective topology and weight evolution
A Salih, A Moshaiov - IEEE Transactions on Evolutionary …, 2022 - ieeexplore.ieee.org
The ability of robot motion controllers to quickly adapt to new environments is expected to
extend the applications of mobile robots. Using the concept of transfer optimization, this …
extend the applications of mobile robots. Using the concept of transfer optimization, this …
Robustness Evaluation of Machine Learning Models for Robot Arm Action Recognition in Noisy Environments
In the realm of robot action recognition, identifying distinct but spatially proximate arm
movements using vision systems in noisy environments poses a significant challenge. This …
movements using vision systems in noisy environments poses a significant challenge. This …
Visual large-scale industrial interaction processing
In this work we investigate the coordination of human-machine interactions from a bird's-eye
view using a single panoramic color camera. Our approach replaces conventional physical …
view using a single panoramic color camera. Our approach replaces conventional physical …
Two-dimensional pose estimation of industrial robotic arms in highly dynamic collaborative environments
T Gulde - 2023 - tobias-lib.ub.uni-tuebingen.de
In modern collaborative production environments where industrial robots and humans are
supposed to work hand in hand, it is mandatory to observe the robot's workspace at all …
supposed to work hand in hand, it is mandatory to observe the robot's workspace at all …