AIMC Topic: Neural Networks, Computer

Clear Filters Showing 4661 to 4670 of 31376 articles

How the technologies behind self-driving cars, social networks, ChatGPT, and DALL-E2 are changing structural biology.

BioEssays : news and reviews in molecular, cellular and developmental biology
The performance of deep Neural Networks (NNs) in the text (ChatGPT) and image (DALL-E2) domains has attracted worldwide attention. Convolutional NNs (CNNs), Large Language Models (LLMs), Denoising Diffusion Probabilistic Models (DDPMs)/Noise Conditio...

Artificial neural network-based prediction of multiple sclerosis using blood-based metabolomics data.

Multiple sclerosis and related disorders
Multiple sclerosis (MS) remains a challenging neurological condition for diagnosis and management and is often detected in late stages, delaying treatment. Artificial intelligence (AI) is emerging as a promising approach to extracting MS information ...

Distance guided generative adversarial network for explainable medical image classifications.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Despite the potential benefits of data augmentation for mitigating data insufficiency, traditional augmentation methods primarily rely on prior intra-domain knowledge. On the other hand, advanced generative adversarial networks (GANs) generate inter-...

Boolean Computation in Single-Transistor Neuron.

Advanced materials (Deerfield Beach, Fla.)
Brain neurons exhibit far more sophisticated and powerful information-processing capabilities than the simple integrators commonly modeled in neuromorphic computing. A biological neuron can in fact efficiently perform Boolean algebra, including linea...

Neural network and layer-wise relevance propagation reveal how ice hockey protective equipment restricts players' motion.

PloS one
Understanding the athlete's movements and the restrictions incurred by protective equipment is crucial for improving the equipment and subsequently, the athlete's performance. The task of equipment improvement is especially challenging in sports incl...

BCCHI-HCNN: Breast Cancer Classification from Histopathological Images Using Hybrid Deep CNN Models.

Journal of imaging informatics in medicine
Breast cancer is the most common cancer in women globally, imposing a significant burden on global public health due to high death rates. Data from the World Health Organization show an alarming annual incidence of nearly 2.3 million new cases, drawi...

Deep self-organizing map neural networks improve the segmentation for inadequate plantar pressure imaging data set.

Network (Bristol, England)
This study introduces a deep self-organizing map neural network based on level-set (LS-SOM) for the customization of a shoe-last defined from plantar pressure imaging data. To alleviate the over-segmentation problem of images, which refers to segment...

Clinical target volume (CTV) automatic delineation using deep learning network for cervical cancer radiotherapy: A study with external validation.

Journal of applied clinical medical physics
PURPOSE: To explore the accuracy and feasibility of a proposed deep learning (DL) algorithm for clinical target volume (CTV) delineation in cervical cancer radiotherapy and evaluate whether it can perform well in external cervical cancer and endometr...

A genetic programming Rician noise reduction and explainable deep learning model for Alzheimer's diseases severity prediction.

Journal of Alzheimer's disease : JAD
BACKGROUND: Degradation of magnetic resonance imaging (MRI) remains a challenging issue, with noise being a key damaging component introduced due to a variety of environmental and mechanical factors.

Inspiration from Visual Ecology for Advancing Multifunctional Robotic Vision Systems: Bio-inspired Electronic Eyes and Neuromorphic Image Sensors.

Advanced materials (Deerfield Beach, Fla.)
In robotics, particularly for autonomous navigation and human-robot collaboration, the significance of unconventional imaging techniques and efficient data processing capabilities is paramount. The unstructured environments encountered by robots, cou...