Results 61 to 70 of about 250,191 (314)

Normalized Convolutional Neural Network

CoRR, 2020
We introduce a Normalized Convolutional Neural Layer, a novel approach to normalization in convolutional networks. Unlike conventional methods, this layer normalizes the rows of the im2col matrix during convolution, making it inherently adaptive to sliced inputs and better aligned with kernel structures. This distinctive approach differentiates it from
Dongsuk Kim, Geonhee Lee, Myungjae Lee, Shin Uk Kang, Dongmin Kim   +4 more
openaire   +2 more sources

SF-ICNN: Spectral–Fractal Iterative Convolutional Neural Network for Classification of Hyperspectral Images [PDF]

One primary concern in the field of remote-sensing image processing is the precise classification of hyperspectral images (HSIs). Lately, deep-learning models have demonstrated cutting-edge results in HSI classification.
Akbari, Vahid, Behnam Asghari Beirami, Mehran Alizadeh Pirbasti, Alizadeh Pirbasti, Mehran, Asghari Beirami, Behnam, Vahid Akbari   +5 more
core   +1 more source

ST-CNN: Spatial-Temporal Convolutional Neural Network for crowd counting in videos [PDF]

, 2019
The task of crowd counting and density maps estimating from videos is challenging due to severe occlusions, scene perspective distortions and diverse crowd distributions.
Gao, Y, Han, J, Zhang, B, Miao, Y
core   +1 more source

Convolutional neural network related. [PDF]

, 2022
Convolutional neural network related.
Ding Han (4857559), Caili Gong (12769732), Minghua Tian (7277369), Shilong Zhang (8576355), Yushuang Ji (12859582), Yongfeng Wei (2641687), Liang Chen (73736), Xinyu Du (4453507)   +7 more
core   +1 more source

ROLLING BEARING FAULT DIAGNOSIS BASED ON FUSION CNN AND PSO-SVM

Jixie qiangdu, 2021
Aiming at the problem that it is difficult to extract subtle fault features in the process of rolling bearing fault identification,this paper proposes a rolling bearing fault diagnosis method based on fusion convolutional neural network and support ...
WANG YongDing, JIN ZiQi
doaj  

A Machine Learning Approach to Screen for Otitis Media Using Digital Otoscope Images Labelled by an Expert Panel

Diagnostics, 2022
Background: Otitis media includes several common inflammatory conditions of the middle ear that can have severe complications if left untreated. Correctly identifying otitis media can be difficult and a screening system supported by machine learning ...
Josefin Sandström, Hermanus Myburgh, Claude Laurent, De Wet Swanepoel, Thorbjörn Lundberg   +4 more
doaj   +1 more source

An Introduction to Convolutional Neural Networks

CoRR, 2015
10 pages, 5 ...
Keiron O'Shea, Ryan Nash
openaire   +2 more sources

Lip Image Segmentation Based on a Fuzzy Convolutional Neural Network [PDF]

, 2020
Research has shown that the human lip and its movements are a rich source of information related to speech content and speaker's identity. Lip image segmentation, as a fundamental step in many lip-reading and visual speaker authentication systems, is of ...
Liew, AWC, Wang, S, Guan, C
core   +1 more source

Brain Tumor and Glioma Grade Classification Using Gaussian Convolutional Neural Network [PDF]

, 2022
Understanding brain diseases such as categorizing Brain-Tumor (BT) is critical to assess the tumors and facilitate the patient with proper cure as per their categorizations.
Maryam, S., Baker, T., Rizwan, M., AR Javed, Dhiya, O., Aysha, S.   +5 more
core   +1 more source

Three Dimensional Image Reconstruction of Electrical Capacitance Tomography Based on Improved ALEXNET Convolutional Neural Network

Journal of Harbin University of Science and Technology, 2020
A method is proposed that the corresponding AlexNet neural network is trained according to the data of different flow patterns for the problem of slow sample training and low imaging accuracy for the threedimensional image reconstruction algorithm of ...
LI Yan, WANG Lu, LI Jiaqi
doaj   +1 more source