AIMC Topic: Neural Networks, Computer

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Object Relocation Visual Tracking Based on Histogram Filter and Siamese Network in Intelligent Transportation.

Sensors (Basel, Switzerland)
Target detection and tracking algorithms are one of the key technologies in the field of autonomous driving in intelligent transportation, providing important sensing capabilities for vehicle localization and path planning. Siamese network-based trac...

Multi-Currency Integrated Serial Number Recognition Model of Images Acquired by Banknote Counters.

Sensors (Basel, Switzerland)
The objective of this study was to establish an automated system for the recognition of banknote serial numbers by developing a deep learning (DL)-based optical character recognition framework. An integrated serial number recognition model for the ba...

Multiple instance neural networks based on sparse attention for cancer detection using T-cell receptor sequences.

BMC bioinformatics
Early detection of cancers has been much explored due to its paramount importance in biomedical fields. Among different types of data used to answer this biological question, studies based on T cell receptors (TCRs) are under recent spotlight due to ...

Semi-supervised learning for topographic map analysis over time: a study of bridge segmentation.

Scientific reports
Geographical research using historical maps has progressed considerably as the digitalization of topological maps across years provides valuable data and the advancement of AI machine learning models provides powerful analytic tools. Nevertheless, an...

Inverse design of core-shell particles with discrete material classes using neural networks.

Scientific reports
The design of scatterers on demand is a challenging task that requires the investigation and development of novel and flexible approaches. In this paper, we propose a machine learning-assisted optimization framework to design multi-layered core-shell...

Fuzzy inference system (FIS) - long short-term memory (LSTM) network for electromyography (EMG) signal analysis.

Biomedical physics & engineering express
A wide range of application domains,s such as remote robotic control, rehabilitation, and remote surgery, require capturing neuromuscular activities. The reliability of the application is highly dependent on an ability to decode intentions accurately...

Efficient Perturbation Inference and Expandable Network for continual learning.

Neural networks : the official journal of the International Neural Network Society
Although humans are capable of learning new tasks without forgetting previous ones, most neural networks fail to do so because learning new tasks could override the knowledge acquired from previous data. In this work, we alleviate this issue by propo...

Segmentation with mixed supervision: Confidence maximization helps knowledge distillation.

Medical image analysis
Despite achieving promising results in a breadth of medical image segmentation tasks, deep neural networks (DNNs) require large training datasets with pixel-wise annotations. Obtaining these curated datasets is a cumbersome process which limits the a...

Neural network predictions of (n,2n) reaction cross-sections at 14.6 MeV incident neutron energy.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
In this study, we have estimated the (n,2n) reaction cross-section for 14.6 MeV incident neutron energy by using the artificial neural network (ANN) method. We have also predicted the reaction cross-sections whose experimental data are not available ...

Multimodal medical image fusion algorithm based on pulse coupled neural networks and nonsubsampled contourlet transform.

Medical & biological engineering & computing
Combining two medical images from different modalities is more helpful for using the resulting image in the healthcare field. Medical image fusion means combining two or more images coming from multiple sensors. This technology obtains an output imag...