Results 131 to 140 of about 1,582,815 (295)

Multi-Tailed Vision Transformer for Efficient Inference [PDF]

Recently, Vision Transformer (ViT) has achieved promising performance in image recognition and gradually serves as a powerful backbone in various vision tasks. To satisfy the sequential input of Transformer, the tail of ViT first splits each image into a
Wang, Yunke, Xu, Chang, Du, Bo, Wang, Wenyuan   +3 more
core  

Nonlocomotory Robotic Strategies for Dynamic Rotation Control in Terrestrial Robots: A Review

Advanced Robotics Research, EarlyView.
Terrestrial robots increasingly require rapid body rotation to maintain stability and agility in complex environments. This review shows nonlocomotory rotational control strategies that operate without ground contact, including reaction wheels, tails, bars, limbs, and thrusters.
Y. Liang, J. An, X. Zheng, D. Wang, S. Wang, X. Wang, P. Zhu, J. Pei, S. Li, J. Paripurana, Y. Han, Z. Tang, X. Gan, Q. He, X. Ma   +14 more
wiley   +1 more source

Improving the Robustness of Visual Teach‐and‐Repeat Navigation Using Drift Error Correction and Event‐Based Vision for Low‐Light Environments

Advanced Robotics Research, EarlyView.
Visual teach‐and‐repeat (VTR) navigation allows robots to learn and follow routes without building a full metric map. We show that navigation accuracy for VTR can be improved by integrating a topological map with error‐drift correction based on stereo vision.
Fuhai Ling, Ze Huang, Tony J. Prescott
wiley   +1 more source

A self attention based deep learning framework for accurate and efficient dental disease detection in OPG radiographs

Scientific Reports
Oral diseases are increasing now-a-days and there is a high demand for the automatic diagnostic system that helps the clinician to detect these oral diseases with more accuracy and reduced human error.
Ramasubramanian Bhoopalan, S. Mirdula, Priyadharshini Kannusamy, D. Gayathri, D. Manikandan, Krishnaraj Ramaswamy   +5 more
doaj   +1 more source

Brain Stroke Classification Using CT Scans with Transformer-Based Models and Explainable AI

Diagnostics
Background & Objective: Stroke remains a leading cause of mortality and long-term disability worldwide, demanding rapid and accurate diagnosis to improve patient outcomes.
Shomukh Qari, Maha A. Thafar
doaj   +1 more source

Soft Actuators Integrated with Control and Power Units: Approaching Wireless Autonomous Soft Robots

Advanced Robotics Research, EarlyView.
Soft robots exhibit significant development potential in various applications. However, there are still key technical challenges regarding material improvement, structure design and components integration. This review focuses on the development and challenge of soft actuators, power components, and control components in untethered intelligent soft ...
Renwu Shi, Feifei Pan, Xiaobin Ji
wiley   +1 more source

A Review of Transformer-Based Models for Computer Vision Tasks: Capturing Global Context and Spatial Relationships [PDF]

Transformer-based models have transformed the landscape of natural language processing (NLP) and are increasingly applied to computer vision tasks with remarkable success.
Pereira, Gracile Astlin, Hussain, Muhammad   +1 more
core   +1 more source

EEViT: Efficient Enhanced Vision Transformer Architectures with Information Propagation and Improved Inductive Bias

AI
The Transformer architecture has been the foundational cornerstone of the recent AI revolution, serving as the backbone of Large Language Models, which have demonstrated impressive language understanding and reasoning capabilities.
Rigel Mahmood, Sarosh Patel, Khaled Elleithy   +2 more
doaj   +1 more source

Retina Vision Transformer (RetinaViT): Introducing Scaled Patches into Vision Transformers

CoRR
Humans see low spatial frequency components before high spatial frequency components. Drawing on this neuroscientific inspiration, we investigate the effect of introducing patches from different spatial frequencies into Vision Transformers (ViTs). We name this model Retina Vision Transformer (RetinaViT) due to its inspiration from the human visual ...
Yuyang Shu, Michael E. Bain
openaire   +3 more sources

Identifying Physical Interactions in Contact‐Based Robot Manipulation for Learning from Demonstration

Advanced Robotics Research, EarlyView.
Robots can learn manipulation tasks from human demonstrations. This work proposes a versatile method to identify the physical interactions that occur in a demonstration, such as sequences of different contacts and interactions with mechanical constraints.
Alex Harm Gert‐Jan Overbeek, Herman van der Kooij, Douwe Dresscher, Mark Vlutters   +3 more
wiley   +1 more source