Results 31 to 40 of about 683,409 (316)

Deep learning-based fully automatic segmentation of wrist cartilage in MR images

, 2020
The study objective was to investigate the performance of a dedicated convolutional neural network (CNN) optimized for wrist cartilage segmentation from 2D MR images.
Andreychenko, Anna, Bendahan, David, Brui, Ekaterina, Efimtcev, Aleksandr Y., Fernandez, Remi, Fokin, Vladimir A., Levchuk, Anatoliy G., Mattei, Jean. P., Melchakova, Irina V., Ogier, Augustin C., Samsonov, Alexey A.   +10 more
core   +3 more sources

A convolutional neural network based deep learning methodology for recognition of partial discharge patterns from high voltage cables [PDF]

, 2019
It is a great challenge to differentiate partial discharge (PD) induced by different types of insulation defects in high-voltage cables. Some types of PD signals have very similar characteristics and are specifically difficult to differentiate, even for ...
Bhatti, Ashfaque Ahmed, Hepburn, Donald M., Judd, Martin D., Li, Lee, Li, Zhaohui, Peng, Xiaosheng, Reid, Alistair J., Siew, Wah Hoon, Wang, Ganjun, Wu, Yijiang, Yang, Fan, Zhou, Chengke   +11 more
core   +4 more sources

TRAFFIC SIGN RECOGNITION WITH CONVOLUTIONAL NEURAL NETWORK

Scientific Journal of Astana IT University, 2022
Road sign recognition is one of the most important steps drivers can take to avoid dangerous roads or accidents. The purpose of the research work is to develop a recognition system, increasing the classification accuracy of the model, using deep learning
Sharipa Temirgaziyeva, Batyrkhan Omarov
doaj   +1 more source

Automatic learning of gait signatures for people identification [PDF]

, 2016
This work targets people identification in video based on the way they walk (i.e. gait). While classical methods typically derive gait signatures from sequences of binary silhouettes, in this work we explore the use of convolutional neural networks (CNN)
Castro, F. M., de la Blanca, N. Perez, Guil, N., Marin-Jimenez, M. J.   +3 more
core   +2 more sources

Mask R-CNN

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017
We present a conceptually simple, flexible, and general framework for object instance segmentation. Our approach efficiently detects objects in an image while simultaneously generating a high-quality segmentation mask for each instance. The method, called Mask R-CNN, extends Faster R-CNN by adding a branch for predicting an object mask in parallel with
Kaiming He, Georgia Gkioxari, Piotr Dollar, Ross Girshick   +3 more
openaire   +4 more sources

Solar Energy Forecast for Integration of Grid and Balancing Power Using Profound Learning [PDF]

E3S Web of Conferences
The rapid and unexpected advancements in solar photovoltaic (PV) technology pose a future challenge for power sector experts responsible for managing the distribution of electricity, given the technology’s direct reliance on atmospheric and weather ...
Shwetabh Kumar, Pathrotkar Nikita
doaj   +1 more source

One-to-many face recognition with bilinear CNNs

, 2016
The recent explosive growth in convolutional neural network (CNN) research has produced a variety of new architectures for deep learning. One intriguing new architecture is the bilinear CNN (B-CNN), which has shown dramatic performance gains on certain ...
Learned-Miller, Erik, Lin, Tsung-Yu, Maji, Subhransu, RoyChowdhury, Aruni   +3 more
core   +1 more source

Safeguarding Critical Infrastructures: Machine Learning in Cybersecurity [PDF]

E3S Web of Conferences
It has become essential to protect vital infrastructures from cyber threats in an age where technology permeates every aspect of our lives. This article examines how machine learning and cybersecurity interact, providing a thorough overview of how this ...
Kalnawat Aarti, Dhabliya Dharmesh, Vydehi Kasichainula, Dhablia Anishkumar, Kumar Santosh D.   +4 more
doaj   +1 more source

A Genetic Programming Approach to Designing Convolutional Neural Network Architectures

, 2017
The convolutional neural network (CNN), which is one of the deep learning models, has seen much success in a variety of computer vision tasks. However, designing CNN architectures still requires expert knowledge and a lot of trial and error.
Bergstra James, Bergstra James, Goodfellow Ian J., Ioffe Sergey, Julian, Kingma Diederik, Lin Min, Mnih Volodymyr, Nair Vinod, Schaffer J. David, Snoek Jasper, Tokui Seiya, Zhang Richard   +12 more
core   +1 more source

Diffusion Tractography Biomarker for Epilepsy Severity in Children With Drug‐Resistant Epilepsy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To develop a novel deep‐learning model of clinical DWI tractography that can accurately predict the general assessment of epilepsy severity (GASE) in pediatric drug‐resistant epilepsy (DRE) and test if it can screen diverse neurocognitive impairments identified through neuropsychological assessments.
Jeong‐Won Jeong, Min‐Hee Lee, Hiroshi Uda, Yoon Ho Hwang, Michael Behen, Aimee Luat, Csaba Juhász, Eishi Asano   +7 more
wiley   +1 more source