Results 131 to 140 of about 204,781 (309)

Rede neural por convolução para reconstrução estéreo [PDF]

, 2000
Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico.Para a modelagem de redes neurais para aplicações de problemas invariantes à translação utilizamos restrições de compartilhamento de pesos.
Otuyama, Júlio Massayuki
core  

Fixed point actions from convolutional neural networks [PDF]

Lattice gauge-equivariant convolutional neural networks (L-CNNs) can be used to form arbitrarily shaped Wilson loops and can approximate any gauge-covariant or gauge-invariant function on the lattice.
Holland, K., Wenger, U., Ipp, A., Müller, D. I.   +3 more
core   +1 more source

The Future of Research in Cognitive Robotics: Foundation Models or Developmental Cognitive Models?

Advanced Robotics Research, EarlyView.
Research in cognitive robotics founded on principles of developmental psychology and enactive cognitive science would yield what we seek in autonomous robots: the ability to perceive its environment, learn from experience, anticipate the outcome of events, act to pursue goals, and adapt to changing circumstances without resorting to training with ...
David Vernon
wiley   +1 more source

An Embedded Inference Framework for Convolutional Neural Network Applications

IEEE Access, 2019
With the rapid development of deep convolutional neural networks, more and more computer vision tasks have been well resolved. These convolutional neural network solutions rely heavily on the performance of the hardware. However, due to privacy issues or
Sheng Bi, Yingjie Zhang, Min Dong, Huaqing Min   +3 more
doaj   +1 more source

Facial emotion recognition using convolutional neural networks [PDF]

, 2021
A lot of progress has been made in the field of Facial Emotion Recognition (FER) in the last decade with the advent of Deep Neural Networks (DNN) and Convolutional Neural Networks (CNN).
Sogalad, Prasad
core  

3D Printing of Soft Robotic Systems: Advances in Fabrication Strategies and Future Trends

Advanced Robotics Research, EarlyView.
Collectively, this review systematically examines 3D‐printed soft robotics, encompassing material selections, function integration, and manufacturing methodologies. Meanwhile, fabrication strategies are analyzed in order of increasing complexity, highlighting persistent challenges with proposed solutions.
Changjiang Liu, Bin Cui, Xumin Huang, Xiaoyu (Rayne) Zheng, T. Thang Vo‐Doan, Ruirui Qiao   +5 more
wiley   +1 more source

Structured learning via convolutional neural networks for vehicle detection [PDF]

, 2017
One of the main tasks in a vision-based traffic monitoring system is the detection of vehicles. Recently, deep neural networks have been successfully applied to this end, outperforming previous approaches.
Ana I. Maqueda, García Santos, Narciso, Jaureguizar Núñez, Fernando, Carlos R. del Blanco, Fernando Jaureguizar, Maqueda Nieto, Ana Isabel, Blanco Adán, Carlos Roberto del, Narciso García   +7 more
core   +1 more source

A Review on Sensor Technologies, Control Approaches, and Emerging Challenges in Soft Robotics

Advanced Robotics Research, EarlyView.
This review provides an introspective of sensors and controllers in soft robotics. Initially describing the current sensing methods, then moving on to the control methods utilized, and finally ending with challenges and future directions in soft robotics focusing on the material innovations, sensor fusion, and embedded intelligence for sensors and ...
Ean Lovett, Maxwell Hammond, Niloufar Seyfi, Amirreza Fahim Golestaneh, Venanzio Cichella, Caterina Lamuta   +5 more
wiley   +1 more source

Fine Tuning Hyperparameters of Deep Learning Models Using Metaheuristic Accelerated Particle Swarm Optimization Algorithm

IEEE Access
In recent years, Convolutional Neural Networks (CNNs) have emerged as powerful tools for solving complex real-world problems, particularly in the domain of image processing.
Abdel-Hamid M. Emara, Ghada Atteia, Jawad Hasan Alkhateeb   +2 more
doaj   +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