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Unsupervised deep learning supports reclassification of Bronze age cypriot writing system.

PloS one
Ancient undeciphered scripts present problems of different nature, not just tied to linguistic identification. The undeciphered Cypro-Minoan script from second millennium BCE Cyprus, for instance, currently does not have a standardized, definitive in...

Fully body visual self-modeling of robot morphologies.

Science robotics
Internal computational models of physical bodies are fundamental to the ability of robots and animals alike to plan and control their actions. These "self-models" allow robots to consider outcomes of multiple possible future actions without trying th...

Student Education Management Strategy Based on Artificial Intelligence Information Model under the Support of 5G Wireless Network.

Computational intelligence and neuroscience
With the popularity of the Internet and the advancement of information technology, more and more people are accepting the teaching and sharing of knowledge through the digitalization of information. The widespread adoption of 5G technology has pushed...

Trends and frontiers of atmospheric duct research based on CiteSpace and deep learning.

Environmental science and pollution research international
The research of evaporation duct is of fundamental importance in the radar and signal communication industry. Particularly, in a real atmosphere environment, most of the radar holes cannot be corrected in time because of the persistent evaporation du...

A Scalable Embedding Based Neural Network Method for Discovering Knowledge From Biomedical Literature.

IEEE/ACM transactions on computational biology and bioinformatics
Nowadays, the amount of biomedical literatures is growing at an explosive speed, and much useful knowledge is yet undiscovered in the literature. Classical information retrieval techniques allow to access explicit information from a given collection ...

idse-HE: Hybrid embedding graph neural network for drug side effects prediction.

Journal of biomedical informatics
In drug development, unexpected side effects are the main reason for the failure of candidate drug trials. Discovering potential side effects of drugsin silicocan improve the success rate of drug screening. However, most previous works extracted and ...

Deep neural networks to recover unknown physical parameters from oscillating time series.

PloS one
Deep neural networks are widely used in pattern-recognition tasks for which a human-comprehensible, quantitative description of the data-generating process, cannot be obtained. While doing so, neural networks often produce an abstract (entangled and ...

Fuzzy-Logic-Based Recommendation System for Processing in Condition Monitoring.

Sensors (Basel, Switzerland)
The development of a machine's condition monitoring system is often a challenging task. This process requires the collection of a sufficiently large dataset on signals from machine operation, context information related to the operation conditions, a...

Knowledge Distillation and Student-Teacher Learning for Visual Intelligence: A Review and New Outlooks.

IEEE transactions on pattern analysis and machine intelligence
Deep neural models, in recent years, have been successful in almost every field, even solving the most complex problem statements. However, these models are huge in size with millions (and even billions) of parameters, demanding heavy computation pow...

Triple-Memory Networks: A Brain-Inspired Method for Continual Learning.

IEEE transactions on neural networks and learning systems
Continual acquisition of novel experience without interfering with previously learned knowledge, i.e., continual learning, is critical for artificial neural networks, while limited by catastrophic forgetting. A neural network adjusts its parameters w...