Results 11 to 20 of about 54,400 (268)

Going Deeper with Dense Connectedly Convolutional Neural Networks for Multispectral Pansharpening

Remote Sensing, 2019
In recent years, convolutional neural networks (CNNs) have shown promising performance in the field of multispectral (MS) and panchromatic (PAN) image fusion (MS pansharpening).
Dong Wang, Ying Li, Li Ma, Zongwen Bai, Jonathan Cheung-Wai Chan   +4 more
doaj   +1 more source

Dynamic-DSO: Direct Sparse Odometry Using Objects Semantic Information for Dynamic Environments

Applied Sciences, 2020
Traditional Simultaneous Localization and Mapping (SLAM) (with loop closure detection), or Visual Odometry (VO) (without loop closure detection), are based on the static environment assumption.
Chao Sheng, Shuguo Pan, Wang Gao, Yong Tan, Tao Zhao   +4 more
doaj   +1 more source

Synergetic effect of adsorption and photocatalysis by zinc ferrite-anchored graphitic carbon nitride nanosheet for the removal of ciprofloxacin under visible light irradiation

Open Chemistry, 2023
Ciprofloxacin (CIP) belongs to the fluoroquinolone antibiotic family. It is mostly used for the treatment of bacterial infections and highly recalcitrant to naturally decompose.
Tamyiz Muchammad, Doong Ruey-an
doaj   +1 more source

CNNs Avoid the Curse of Dimensionality by Learning on Patches

IEEE Open Journal of Signal Processing, 2023
Despite the success of convolutional neural networks (CNNs) in numerous computer vision tasks and their extraordinary generalization performances, several attempts to predict the generalization errors of CNNs have only been limited to a posteriori ...
Vamshi C. Madala, Shivkumar Chandrasekaran, Jason Bunk   +2 more
doaj   +1 more source

Botulinum Toxin Suppression of CNS Network Activity In Vitro

Journal of Toxicology, 2014
The botulinum toxins are potent agents which disrupt synaptic transmission. While the standard method for BoNT detection and quantification is based on the mouse lethality assay, we have examined whether alterations in cultured neuronal network activity ...
Joseph J. Pancrazio, Kamakshi Gopal, Edward W. Keefer, Guenter W. Gross   +3 more
doaj   +1 more source

Recognizing New Classes with Synthetic Data in the Loop: Application to Traffic Sign Recognition

Sensors, 2020
On-board vision systems may need to increase the number of classes that can be recognized in a relatively short period. For instance, a traffic sign recognition system may suddenly be required to recognize new signs.
Gabriel Villalonga, Joost Van de Weijer, Antonio M. López   +2 more
doaj   +1 more source

Convolutional Neural Networks: A Survey

Computers, 2023
Artificial intelligence (AI) has become a cornerstone of modern technology, revolutionizing industries from healthcare to finance. Convolutional neural networks (CNNs) are a subset of AI that have emerged as a powerful tool for various tasks including ...
Moez Krichen
doaj   +1 more source

A Comprehensive Review on the Application of 3D Convolutional Neural Networks in Medical Imaging

Engineering Proceedings, 2023
Convolutional Neural Networks (CNNs) are kinds of deep learning models that were created primarily for processing and evaluating visual input, which makes them extremely applicable in the field of medical imaging.
Satyam Tiwari, Goutam Jain, Dasharathraj K. Shetty, Manu Sudhi, Jayaraj Mymbilly Balakrishnan, Shreepathy Ranga Bhatta   +5 more
doaj   +1 more source

Chronotherapy Network Netherlands (CNN) [PDF]

Journal of Biological Rhythms, 2019
Information is provided about the Chronotherapy Network Netherlands (CNN).
Ybe Meesters, Danielle Starreveld, Esmée Verwijk, Harm-Pieter Spaans, Marijke C. M. Gordijn   +4 more
openaire   +7 more sources

A survey of remote sensing image classification based on CNNs

Big Earth Data, 2019
With the development of earth observation technologies, the acquired remote sensing images are increasing dramatically, and a new era of big data in remote sensing is coming.
Jia Song, Shaohua Gao, Yunqiang Zhu, Chenyan Ma   +3 more
doaj   +1 more source