AIMC Topic: Neural Networks, Computer

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Signal automatic modulation based on AMC neural network fusion.

PloS one
With the rapid development of modern communication technology, it has become a core problem in the field of communication to find new ways to effectively modulate signals and to classify and recognize the results of automatic modulation. To further i...

Enhancing Skin Cancer Diagnosis Using Swin Transformer with Hybrid Shifted Window-Based Multi-head Self-attention and SwiGLU-Based MLP.

Journal of imaging informatics in medicine
Skin cancer is one of the most frequently occurring cancers worldwide, and early detection is crucial for effective treatment. Dermatologists often face challenges such as heavy data demands, potential human errors, and strict time limits, which can ...

Deep Learning Models of Multi-Scale Lesion Perception Attention Networks for Diagnosis and Staging of Pneumoconiosis: A Comparative Study with Radiologists.

Journal of imaging informatics in medicine
Accurate prediction of pneumoconiosis is essential for individualized early prevention and treatment. However, the different manifestations and high heterogeneity among radiologists make it difficult to diagnose and stage pneumoconiosis accurately. H...

Nonlinear classifiers for wet-neuromorphic computing using gene regulatory neural network.

Biophysical reports
The gene regulatory network (GRN) of biological cells governs a number of key functionalities that enable them to adapt and survive through different environmental conditions. Close observation of the GRN shows that the structure and operational prin...

Chaotic neural network algorithm with competitive learning integrated with partial Least Square models for the prediction of the toxicity of fragrances in sanitizers and disinfectants.

The Science of the total environment
This study addresses the need for accurate structural data regarding the toxicity of fragrances in sanitizers and disinfectants. We compare the predictive and descriptive (model stability) potential of multiple linear regression (MLR) and partial lea...

Physics-informed neural networks for parameter estimation in blood flow models.

Computers in biology and medicine
BACKGROUND: Physics-informed neural networks (PINNs) have emerged as a powerful tool for solving inverse problems, especially in cases where no complete information about the system is known and scatter measurements are available. This is especially ...

Transformers and large language models in healthcare: A review.

Artificial intelligence in medicine
With Artificial Intelligence (AI) increasingly permeating various aspects of society, including healthcare, the adoption of the Transformers neural network architecture is rapidly changing many applications. Transformer is a type of deep learning arc...

A Multi-Level Interpretable Sleep Stage Scoring System by Infusing Experts' Knowledge Into a Deep Network Architecture.

IEEE transactions on pattern analysis and machine intelligence
In recent years, deep learning has shown potential and efficiency in a wide area including computer vision, image and signal processing. Yet, translational challenges remain for user applications due to a lack of interpretability of algorithmic decis...

VNVC: A Versatile Neural Video Coding Framework for Efficient Human-Machine Vision.

IEEE transactions on pattern analysis and machine intelligence
Almost all digital videos are coded into compact representations before being transmitted. Such compact representations need to be decoded back to pixels before being displayed to humans and - as usual - before being enhanced/analyzed by machine visi...

Spatial and geometric learning for classification of breast tumors from multi-center ultrasound images: a hybrid learning approach.

BMC medical imaging
BACKGROUND: Breast cancer is the most common cancer among women, and ultrasound is a usual tool for early screening. Nowadays, deep learning technique is applied as an auxiliary tool to provide the predictive results for doctors to decide whether to ...