AIMC Topic: Neural Networks, Computer

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Dermoscopic Image Classification Method Using an Ensemble of Fine-Tuned Convolutional Neural Networks.

Sensors (Basel, Switzerland)
Aiming at the problems of large intra-class differences, small inter-class differences, low contrast, and small and unbalanced datasets in dermoscopic images, this paper proposes a dermoscopic image classification method based on an ensemble of fine-...

Towards universal neural network potential for material discovery applicable to arbitrary combination of 45 elements.

Nature communications
Computational material discovery is under intense study owing to its ability to explore the vast space of chemical systems. Neural network potentials (NNPs) have been shown to be particularly effective in conducting atomistic simulations for such pur...

The geometry of robustness in spiking neural networks.

eLife
Neural systems are remarkably robust against various perturbations, a phenomenon that still requires a clear explanation. Here, we graphically illustrate how neural networks can become robust. We study spiking networks that generate low-dimensional r...

Emergence of associative learning in a neuromorphic inference network.

Journal of neural engineering
. In the theoretical framework of predictive coding and active inference, the brain can be viewed as instantiating a rich generative model of the world that predicts incoming sensory data while continuously updating its parameters via minimization of...

Hybrid HCNN-KNN Model Enhances Age Estimation Accuracy in Orthopantomography.

Frontiers in public health
Age estimation in dental radiographs Orthopantomography (OPG) is a medical imaging technique that physicians and pathologists utilize for disease identification and legal matters. For example, for estimating post-mortem interval, detecting child abus...

Training a Feedforward Neural Network Using Hybrid Gravitational Search Algorithm with Dynamic Multiswarm Particle Swarm Optimization.

BioMed research international
One of the most well-known methods for solving real-world and complex optimization problems is the gravitational search algorithm (GSA). The gravitational search technique suffers from a sluggish convergence rate and weak local search capabilities wh...

Traffic Sign Detection Based on SSD Combined with Receptive Field Module and Path Aggregation Network.

Computational intelligence and neuroscience
The traditional traffic sign detection algorithm can not deal with the application scenarios such as intelligent transportation system or advanced assisted driving environment, and it is difficult to meet the application requirements in detection acc...

Optimal Deep Transfer Learning-Based Human-Centric Biomedical Diagnosis for Acute Lymphoblastic Leukemia Detection.

Computational intelligence and neuroscience
Human-centric biomedical diagnosis (HCBD) becomes a hot research topic in the healthcare sector, which assists physicians in the disease diagnosis and decision-making process. Leukemia is a pathology that affects younger people and adults, instigatin...

Symmetric Convolutional and Adversarial Neural Network Enables Improved Mental Stress Classification From EEG.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Electroencephalography (EEG) is widely used for mental stress classification, but effective feature extraction and transfer across subjects remain challenging due to its variability. In this paper, a novel deep neural network combining convolutional ...

Comparative Study of Structural Anomaly Diagnosis Based on ANN Model Using Random Displacement and Acceleration Responses with Incomplete Measurements.

Sensors (Basel, Switzerland)
Structural anomaly diagnosis, such as damage identification, is a continuously interesting issue. Artificial neural networks have an excellent ability to model complex structure dynamics. In this paper, an artificial neural network model is used to d...