Results 51 to 60 of about 3,700 (260)

Bidirectional Process Prediction in the Laser‐Induced‐Graphene Production Using Blackbox Deep Learning

Advanced Materials Technologies, EarlyView.
This study shows that a lightweight blackbox neural network provides a practical, cost‐effective solution for bidirectional process prediction in laser‐induced graphene (LIG) fabrication. Achieving high predictive performance with minimal overhead, the approach democratizes machine learning (ML) for resource‐limited environments.
Maxim Polomoshnov, Nitheesh M. Nair, Gerardo Hernández‐Sosa, Markus Reischl   +3 more
wiley   +1 more source

THE UTILIZATION OF MACHINE LEARNING FOR NETWORK INTRUSION DETECTION SYSTEMS

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
This study investigates the integration of Multilayer Perceptron (MLP) architecture in Network Intrusion Detection Systems (NIDS) to strengthen cyber defences against evolving threats.
Ahmad Sanmorino, Herri Setiawan, John Roni Coyanda   +2 more
doaj   +1 more source

An extended class of multilayer perceptron [PDF]

Neurocomputing, 2008
In this work an extended class of multilayer perceptron is presented. This includes independent parameters, boundary conditions and lower and upper bounds. In some cases, such extensions contain a priori information of the problem. On some other situations they are necessary in order to define a correct representation for the solution. The use of
Roberto Lopez, Eugenio Oñate
openaire   +2 more sources

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

Probabilistic Multilayer Perceptrons for Wind Farm Condition Monitoring

Wind Energy
We provide a condition monitoring system for wind farms, based on normal behaviour modelling using a probabilistic multilayer perceptron with transfer learning via fine‐tuning.
Filippo Fiocchi, Domniki Ladopoulou, Petros Dellaportas   +2 more
doaj   +1 more source

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

Prunability of Multi-Layer Perceptrons Trained with the Forward-Forward Algorithm

Mathematics
We explore the sparsity and prunability of multi-layer perceptrons (MLPs) trained using the Forward-Forward (FF) algorithm, an alternative to backpropagation (BP) that replaces the backward pass with local, contrastive updates at each layer.
Mitko Nikov, Damjan Strnad, David Podgorelec   +2 more
doaj   +1 more source

Continual Learning for Multimodal Data Fusion of a Soft Gripper

Advanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

Backpropagation Through Soft Body: Investigating Information Processing in Brain–Body Coupling Systems

Advanced Robotics Research, EarlyView.
This study explores how information processing is distributed between brains and bodies through a codesign approach. Using the “backpropagation through soft body” framework, brain–body coupling agents are developed and analyzed across several tasks in which output is generated through the agents’ physical dynamics.
Hiroki Tomioka, Katsuma Inoue, Yasuo Kuniyoshi, Kohei Nakajima   +3 more
wiley   +1 more source

Design of real and complex recurrent neural networks for sound source localisation [PDF]

JASA Express Letters
This study explores a pruning technique based on the singular value decomposition for both real- and complex-valued recurrent neural networks (RNNs).
Vlad S. Paul, Philip A. Nelson
doaj   +1 more source