Wood identification is regularly performed by observing the wood anatomy, such as colour, texture, fibre direction, and other characteristics. The manual process, however, could be time consuming, especially when work required at high quantity. Considering this condition, a convolutional neural networks (CNN)-based program applied to improve image classification results. research focuses on alg...

Recently, researchers, specialists, and companies around the world are rolling out deep learning image processing-based systems that can fastly process hundreds of X-Ray Computed Tomography (CT) images to accelerate diagnosis pneumonia such as SARS, covid-19, etc., aid in its containment. Medical analysis is one most promising research areas; it provides facilities for making decisions several ...

The development of science and technology (IPTEK) in the current era is growing very rapidly various fields such as industry, education, especially health sector. Many technologies can be used, one which artificial intelligence technology. This study aims to detect skin cancer images using CNN so that they efficient precise. research method uses convolutional neural network (CNN) method, namely...

Groenhoff, MSN, MBA, RN, CNN (South Florida Flamingo Chapter), Sue McManus, MSN, CFNP, CNN (Acadiana Chapter); and Janie Martinez, BSN, RN, CCRN, CNN (Alamo Chapter); ANNA members Emily Hodgin, BSN, RN, CNN, CPHQ (Cardinal Chapter); Carmen Mejias, BSN, RN, CNN (Heart of Texas Chapter); Betsy King, MSN, RN, CNN; (Northeast TriState Chapter); Darene Hall, MSN, RN, CNN (Chumash Chapter); and Glady...

A systematic design methodology for finding CNN parameters with prescribed functions is proposed. A given function (task) is translated into several local operations, and they are realized as stable states of the CNN system. Many CNN parameters (CNN genes) with the same functions can be easily derived by using this design methodology. A genetic algorithm based CNN gene design methodology is als...

During the last few decades, worsening air quality has been diagnosed in many cities around world. The accurately prediction of pollutants, particularly, particulate matter 2.5 (PM2.5) is extremely important for environmental management. A Convolutional Neural Network (CNN) P-CNN model presented this paper, which uses seven different pollutant satellite images, such as Aerosol index (AER AI), M...

Image retrieval using a textual query becomes major challenge mainly due to human perception subjectivity and the impreciseness of image annotations. These drawbacks can be overcome by focusing on content images rather than descriptions images. Traditional feature extraction techniques demand for expert knowledge select limited types are also sensitive changing imaging conditions. Deep Convolut...

This study focused on the possibility of implementing a vision-based architecture to monitor and detect presence trash or valuables in shared cars. The system was introduced take pictures rear seating area four-door passenger car. Image capture performed with stationary wide-angled camera unit, image classification conducted prediction model remote server. For classification, convolutional neur...

Image recognition has been applied to many fields, but it is relatively rarely medical images. Recent significant deep learning progress for image raised strong research interest in recognition. First of all, we found the prediction result using VGG16 model on failed pneumonia X-ray Thus, this paper proposes IVGG13 (Improved Visual Geometry Group-13), a modified classification X-rays Open-sourc...