AIMC Topic: Neural Networks, Computer

Clear Filters Showing 11251 to 11260 of 31376 articles

RadioBERT: A deep learning-based system for medical report generation from chest X-ray images using contextual embeddings.

Journal of biomedical informatics
BACKGROUND: Increasing number of chest X-ray (CXR) examinations in radiodiagnosis departments burdens radiologists' and makes the timely generation of accurate radiological reports highly challenging. An automatic radiological report generation (ARRG...

Decomposing predictability to identify dominant causal drivers in complex ecosystems.

Proceedings of the National Academy of Sciences of the United States of America
Ecosystems are complex systems of various physical, biological, and chemical processes. Since ecosystem dynamics are composed of a mixture of different levels of stochasticity and nonlinearity, handling these data is a challenge for existing methods ...

Machine Learning Approach to Predict the Performance of a Stratified Thermal Energy Storage Tank at a District Cooling Plant Using Sensor Data.

Sensors (Basel, Switzerland)
In the energy management of district cooling plants, the thermal energy storage tank is critical. As a result, it is essential to keep track of TES results. The performance of the TES has been measured using a variety of methodologies, both numerical...

A Comprehensive Review on Lane Marking Detection Using Deep Neural Networks.

Sensors (Basel, Switzerland)
Lane marking recognition is one of the most crucial features for automotive vehicles as it is one of the most fundamental requirements of all the autonomy features of Advanced Driver Assistance Systems (ADAS). Researchers have recently made promising...

Fast and Efficient Image Novelty Detection Based on Mean-Shifts.

Sensors (Basel, Switzerland)
Image novelty detection is a repeating task in computer vision and describes the detection of anomalous images based on a training dataset consisting solely of normal reference data. It has been found that, in particular, neural networks are well-sui...

Automatic identification of benign pigmented skin lesions from clinical images using deep convolutional neural network.

BMC biotechnology
OBJECTIVE: We aimed to develop a computer-aided detection (CAD) system for accurate identification of benign pigmented skin lesions (PSLs) from images captured using a digital camera or a smart phone.

Human Monkeypox Classification from Skin Lesion Images with Deep Pre-trained Network using Mobile Application.

Journal of medical systems
Recently, human monkeypox outbreaks have been reported in many countries. According to the reports and studies, quick determination and isolation of infected people are essential to reduce the spread rate. This study presents an Android mobile applic...

Multicomponent Raman spectral regression using complete and incomplete models and convolutional neural networks.

The Analyst
With the advent of hyperspectral Raman imaging technology, especially the rapid and high-resolution imaging schemes, datasets with thousands to millions of spectra are now commonplace. Standard preprocessing and regression methods such as least squar...

Structured random receptive fields enable informative sensory encodings.

PLoS computational biology
Brains must represent the outside world so that animals survive and thrive. In early sensory systems, neural populations have diverse receptive fields structured to detect important features in inputs, yet significant variability has been ignored in ...

Classification of Multiclass Histopathological Breast Images Using Residual Deep Learning.

Computational intelligence and neuroscience
Pathologists need a lot of clinical experience and time to do the histopathological investigation. AI may play a significant role in supporting pathologists and resulting in more accurate and efficient histopathological diagnoses. Breast cancer is on...