AIMC Topic: Neural Networks, Computer

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An improved sample selection framework for learning with noisy labels.

PloS one
Deep neural networks have powerful memory capabilities, yet they frequently suffer from overfitting to noisy labels, leading to a decline in classification and generalization performance. To address this issue, sample selection methods that filter ou...

Classification of offshore wind grid-connected power quality disturbances based on fast S-transform and CPO-optimized convolutional neural network.

PloS one
The large-scale integration of offshore wind power into the power grid has brought serious challenges to the power system power quality. Aiming at the problem of power quality disturbance detection and classification, this paper proposes a novel algo...

Topology aware multitask cascaded U-Net for cerebrovascular segmentation.

PloS one
Cerebrovascular segmentation is a crucial preliminary task for many computer-aided diagnosis tools dealing with cerebrovascular pathologies. Over the last years, deep learning based methods have been widely applied to this task. However, classic deep...

Development and validation of a deep learning algorithm for the classification of the level of surgical difficulty in impacted mandibular third molar surgery.

International journal of oral and maxillofacial surgery
The aim of this study was to develop and validate a convolutional neural network (CNN) algorithm for the detection of impacted mandibular third molars in panoramic radiographs and the classification of the surgical extraction difficulty level. A data...

An adaptive variable-parameter dynamic learning network for solving constrained time-varying QP problem.

Neural networks : the official journal of the International Neural Network Society
To efficiently solve the time-varying convex quadratic programming (TVCQP) problem under equational constraint, an adaptive variable-parameter dynamic learning network (AVDLN) is proposed and analyzed. Being different from existing varying-parameter ...

Deep learning-driven multi-omics sequential diagnosis with Hybrid-OmniSeq: Unraveling breast cancer complexity.

Technology and health care : official journal of the European Society for Engineering and Medicine
BackgroundBreast cancer results from an uncontrolled growth of breast tissue. Many methods of diagnosis are using multi-omics data to better understand the complexity of breast cancer.ObjectiveThe new strategy laid out in this work, called "Hybrid-Om...

Low-power and lightweight spiking transformer for EEG-based auditory attention detection.

Neural networks : the official journal of the International Neural Network Society
EEG signal analysis can be used to study brain activity and the function and structure of neural networks, helping to understand neural mechanisms such as cognition, emotion, and behavior. EEG-based auditory attention detection is using EEG signals t...

Deep clustering analysis via variational autoencoder with Gamma mixture latent embeddings.

Neural networks : the official journal of the International Neural Network Society
This article proposes a novel deep clustering model based on the variational autoencoder (VAE), named GamMM-VAE, which can learn latent representations of training data for clustering in an unsupervised manner. Most existing VAE-based deep clustering...

LCFFNet: A Lightweight Cross-scale Feature Fusion Network for human pose estimation.

Neural networks : the official journal of the International Neural Network Society
Human pose estimation is one of the most critical and challenging problems in computer vision. It is applied in many computer vision fields and has important research significance. However, it is still a difficult challenge to strike a balance betwee...

BIRDNN: Behavior-Imitation Based Repair for Deep Neural Networks.

Neural networks : the official journal of the International Neural Network Society
The increasing utilization of deep neural networks (DNNs) in safety-critical systems has raised concerns about their potential to exhibit undesirable behaviors. Consequently, DNN repair/patching arises in response to the times, and it aims to elimina...