Results 111 to 120 of about 28,970 (210)

A deep learning approach versus expert clinician panel in the classification of posterior circulation infarction

NeuroImage: Clinical
Background: Posterior circulation infarction (POCI) is common. Imaging techniques such as non-contrast-CT (NCCT) and diffusion-weighted-magnetic-resonance-imaging commonly fail to detect hyperacute POCI.
Leon S. Edwards, Milanka Visser, Cecilia Cappelen-Smith, Dennis Cordato, Andrew Bivard, Leonid Churilov, Christopher Blair, James Thomas, Angela Dos Santos, Longting Lin, Chushuang Chen, Carlos Garcia-Esperon, Kenneth Butcher, Tim Kleinig, Phillip MC Choi, Xin Cheng, Qiang Dong, Richard I. Aviv, Mark W. Parsons   +18 more
doaj   +1 more source

DenseNet: Implementing Efficient ConvNet Descriptor Pyramids

, 2014
Convolutional Neural Networks (CNNs) can provide accurate object classification. They can be extended to perform object detection by iterating over dense or selected proposed object regions. However, the runtime of such detectors scales as the total number and/or area of regions to examine per image, and training such detectors may be prohibitively ...
Iandola, Forrest, Moskewicz, Matt, Karayev, Sergey, Girshick, Ross, Darrell, Trevor, Keutzer, Kurt   +5 more
openaire   +2 more sources

Pneumonia Image Classification Using DenseNet Architecture

Information
Pulmonary diseases, including pneumonia, represent a significant health challenge and are often diagnosed using X-rays. This study investigates the effectiveness of artificial intelligence (AI) in enhancing the diagnostic capabilities of X-ray imaging.
Mihai Bundea, Gabriel Mihail Danciu
openaire   +2 more sources

Siamese-Derived Attention Dense Network for Seismic Impedance Inversion

Mathematics
Seismic impedance inversion is essential for providing high-resolution stratigraphic analysis. Therefore, improving the accuracy while ensuring the efficiency of the inversion model is crucial for practical implementation.
Jiang Wu
doaj   +1 more source

Enhancing pancreatic cancer detection in CT images through secretary wolf bird optimization and deep learning

Scientific Reports
The pancreas is a gland in the abdomen that helps to produce hormones and digest food. The irregular development of tissues in the pancreas is termed as pancreatic cancer.
Sandhya Mekala, Phani Kumar S
doaj   +1 more source

Pulse pile-up recognition using multi-module DenseNet in neutron-gamma discrimination

Nuclear Engineering and Technology
Neutron-gamma discrimination is crucial for various applications in nuclear science and technology. Currently, the majority of research is focused on pulse shape discrimination, and conventional methods achieve a certain level of accuracy in conventional
Ye Pan, Pin Gong, Zhimeng Hu, Zeyu Wang, Dajian Liang, Cheng Zhou, Xiaoxiang Zhu, Xiaobin Tang   +7 more
doaj   +1 more source

Exploring DenseNet for Image Captioning

Journal of Electrical Systems
Captioning images is a complicated process in computer vision that necessitates a combination of visual comprehension and language processing. Image captioning is highly useful in various fields like accessibility, robotics, and autonomous systems as it generates text descriptions from images automatically.
openaire   +1 more source

Exploring Feature Reuse in DenseNet Architectures

, 2018
Densely Connected Convolutional Networks (DenseNets) have been shown to achieve state-of-the-art results on image classification tasks while using fewer parameters and computation than competing methods. Since each layer in this architecture has full access to the feature maps of all previous layers, the network is freed from the burden of having to ...
openaire   +2 more sources

Automated detection of C-shaped canals in mandibular second molars from panoramic radiographs: comparing single and ensemble convolutional neural networks within a 2-stage pipeline. [PDF]

Clin Oral Investig
Çakmak YE, Er K.
europepmc   +1 more source

A Hybrid Deep Learning Framework for Automated Dental Disorder Diagnosis from X-Ray Images. [PDF]

J Clin Med
El-Aziz AAA, Elmogy M, Mahmood MA, El-Ghany SA.   +3 more
europepmc   +1 more source