A state-of-the-art review on mobile robotics tasks using artificial intelligence and visual data
Nowadays, the field of mobile robotics has experienced an important evolution and these
robots are more commonly proposed to solve different tasks autonomously. The use of …
robots are more commonly proposed to solve different tasks autonomously. The use of …
Convolutional extreme learning machines: A systematic review
Much work has recently identified the need to combine deep learning with extreme learning
in order to strike a performance balance with accuracy, especially in the domain of …
in order to strike a performance balance with accuracy, especially in the domain of …
Token boosting for robust self-supervised visual transformer pre-training
Learning with large-scale unlabeled data has become a powerful tool for pre-training Visual
Transformers (VTs). However, prior works tend to overlook that, in real-world scenarios, the …
Transformers (VTs). However, prior works tend to overlook that, in real-world scenarios, the …
A framework for robotic arm pose estimation and movement prediction based on deep and extreme learning models
IR Rodrigues, M Dantas, AT de Oliveira Filho… - The Journal of …, 2023 - Springer
Human-robot collaboration has gained a notable prominence in Industry 4.0, as the use of
collaborative robots increases efficiency and productivity in the automation process …
collaborative robots increases efficiency and productivity in the automation process …
An experimental evaluation of Siamese Neural Networks for robot localization using omnidirectional imaging in indoor environments
JJ Cabrera, V Román, A Gil, O Reinoso… - Artificial Intelligence …, 2024 - Springer
The objective of this paper is to address the localization problem using omnidirectional
images captured by a catadioptric vision system mounted on the robot. For this purpose, we …
images captured by a catadioptric vision system mounted on the robot. For this purpose, we …
When CNNs meet random RNNs: Towards multi-level analysis for RGB-D object and scene recognition
Recognizing objects and scenes are two challenging but essential tasks in image
understanding. In particular, the use of RGB-D sensors in handling these tasks has emerged …
understanding. In particular, the use of RGB-D sensors in handling these tasks has emerged …
Early or late fusion matters: Efficient rgb-d fusion in vision transformers for 3d object recognition
The Vision Transformer (ViT) architecture has established its place in computer vision
literature, however, training ViTs for RGB-D object recognition remains an understudied …
literature, however, training ViTs for RGB-D object recognition remains an understudied …
Scene recognition mechanism for service robot adapting various families: A cnn-based approach using multi-type cameras
The key challenges of scene recognition for service robots in various family environments
are the view shortage of holistic scenes and poor adaptation. To address these problems, a …
are the view shortage of holistic scenes and poor adaptation. To address these problems, a …
Cross-level multi-modal features learning with transformer for rgb-d object recognition
Object recognition, one of the main goals of robot vision, is a vital prerequisite for service
robots to perform domestic tasks. Thanks to the rich sense of information provided by RGB-D …
robots to perform domestic tasks. Thanks to the rich sense of information provided by RGB-D …
Airobject: A temporally evolving graph embedding for object identification
Object encoding and identification are vital for robotic tasks such as autonomous
exploration, semantic scene understanding, and re-localization. Previous approaches have …
exploration, semantic scene understanding, and re-localization. Previous approaches have …