AIMC Topic: Neural Networks, Computer

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Dual scale light weight cross attention transformer for skin lesion classification.

PloS one
Skin cancer is rapidly growing globally. In the past decade, an automated diagnosis system has been developed using image processing and machine learning. The machine learning methods require hand-crafted features, which may affect performance. Recen...

Temporal spiking generative adversarial networks for heading direction decoding.

Neural networks : the official journal of the International Neural Network Society
The spike-based neuronal responses within the ventral intraparietal area (VIP) exhibit intricate spatial and temporal dynamics in the posterior parietal cortex, presenting decoding challenges such as limited data availability at the biological popula...

Dual-tower model with semantic perception and timespan-coupled hypergraph for next-basket recommendation.

Neural networks : the official journal of the International Neural Network Society
Next basket recommendation (NBR) is an essential task within the realm of recommendation systems and is dedicated to the anticipation of user preferences in the next moment based on the analysis of users' historical sequences of engaged baskets. Curr...

M4Net: Multi-level multi-patch multi-receptive multi-dimensional attention network for infrared small target detection.

Neural networks : the official journal of the International Neural Network Society
The detection of infrared small targets is getting more and more attention, and has a wider application in both military and civilian fields. The traditional infrared small target detection methods heavily rely on the setting of manual features, and ...

An extrapolation-driven network architecture for physics-informed deep learning.

Neural networks : the official journal of the International Neural Network Society
Current physics-informed neural network (PINN) implementations with sequential learning strategies often experience some weaknesses, such as the failure to reproduce the previous training results when using a single network, the difficulty to strictl...

Semi-supervised medical image segmentation network based on mutual learning.

Medical physics
BACKGROUND: Semi-supervised learning provides an effective means to address the challenge of insufficient labeled data in medical image segmentation tasks. However, when a semi-supervised segmentation model is overfitted and exhibits cognitive bias, ...

Self-supervised learning improves robustness of deep learning lung tumor segmentation models to CT imaging differences.

Medical physics
BACKGROUND: Self-supervised learning (SSL) is an approach to extract useful feature representations from unlabeled data, and enable fine-tuning on downstream tasks with limited labeled examples. Self-pretraining is a SSL approach that uses curated do...

Securing healthcare medical image information using advance morphological component analysis, information hiding systems, and hybrid convolutional neural networks on IoMT.

Computers in biology and medicine
Health care images contain a variety of imaging information that has specific features, which can make it challenging to assess and decide on the methods necessitated to safeguard the highly classified visuals from unauthorized exposure during transm...

Design and validation of Withings ECG Software 2, a tiny neural network based algorithm for detection of atrial fibrillation.

Computers in biology and medicine
BACKGROUND: Atrial Fibrillation (AF) is the most common form of arrhythmia in the world with a prevalence of 1%-2%. AF is also associated with an increased risk of cardiovascular diseases (CVD), such as stroke, heart failure, and coronary artery dise...

View-symmetric representations of faces in human and artificial neural networks.

Neuropsychologia
View symmetry has been suggested to be an important intermediate representation between view-specific and view-invariant representations of faces in the human brain. Here, we compared view-symmetry in humans and a deep convolutional neural network (D...