AIMC Topic: Neural Networks, Computer

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Distilling Knowledge From an Ensemble of Vision Transformers for Improved Classification of Breast Ultrasound.

Academic radiology
RATIONALE AND OBJECTIVES: To develop a deep learning model for the automated classification of breast ultrasound images as benign or malignant. More specifically, the application of vision transformers, ensemble learning, and knowledge distillation i...

Parasitic egg recognition using convolution and attention network.

Scientific reports
Intestinal parasitic infections (IPIs) caused by protozoan and helminth parasites are among the most common infections in humans in low-and-middle-income countries. IPIs affect not only the health status of a country, but also the economic sector. Ov...

Synchronization in STDP-driven memristive neural networks with time-varying topology.

Journal of biological physics
Synchronization is a widespread phenomenon in the brain. Despite numerous studies, the specific parameter configurations of the synaptic network structure and learning rules needed to achieve robust and enduring synchronization in neurons driven by s...

Chaos and multi-layer attractors in asymmetric neural networks coupled with discrete fractional memristor.

Neural networks : the official journal of the International Neural Network Society
This article introduces a novel model of asymmetric neural networks combined with fractional difference memristors, which has both theoretical and practical implications in the rapidly evolving field of computational intelligence. The proposed model ...

Adaptive optimal control of affine nonlinear systems via identifier-critic neural network approximation with relaxed PE conditions.

Neural networks : the official journal of the International Neural Network Society
This paper considers an optimal control of an affine nonlinear system with unknown system dynamics. A new identifier-critic framework is proposed to solve the optimal control problem. Firstly, a neural network identifier is built to estimate the unkn...

The CNN model aided the study of the clinical value hidden in the implant images.

Journal of applied clinical medical physics
PURPOSE: This article aims to construct a new method to evaluate radiographic image identification results based on artificial intelligence, which can complement the limited vision of researchers when studying the effect of various factors on clinica...

Oral Cancer Prediction Using a Probability Neural Network (PNN).

Asian Pacific journal of cancer prevention : APJCP
OBJECTIVE: In India, usually, oral cancer is mostly identified at a progressive stage of malignancy. Hence, we are motivated to identify oral cancer in its early stages, which helps to increase the lifetime of the patient, but this early detection is...

HybridSNN: Combining Bio-Machine Strengths by Boosting Adaptive Spiking Neural Networks.

IEEE transactions on neural networks and learning systems
Spiking neural networks (SNNs), inspired by the neuronal network in the brain, provide biologically relevant and low-power consuming models for information processing. Existing studies either mimic the learning mechanism of brain neural networks as c...

Effects of Motion-Relevant Knowledge From Unlabeled Video to Human-Object Interaction Detection.

IEEE transactions on neural networks and learning systems
The existing works on human-object interaction (HOI) detection usually rely on expensive large-scale labeled image datasets. However, in real scenes, labeled data may be insufficient, and some rare HOI categories have few samples. This poses great ch...