Results 111 to 120 of about 6,343,053 (206)

A Face Spoofing Detection Method Based on Domain Adaptation and Lossless Size Adaptation

IEEE Access, 2020
In this paper, a face spoofing detection method called the Fully Convolutional Network with Domain Adaptation and Lossless Size Adaptation (FCN-DA-LSA) is proposed.
Wenyun Sun, Yu Song, Haitao Zhao, Zhong Jin   +3 more
doaj   +1 more source

Individual bird identification by modelling temporal structure in bioacoustic embeddings

Methods in Ecology and Evolution, Volume 17, Issue 10, Page 2909-2927, October 2026.
Abstract Identifying individual animals from vocalizations is an emerging research area in computational bioacoustics. This non‐invasive approach reduces reliance on physical capture and tagging for wildlife monitoring. Recent advances in this area leverage deep learning and bioacoustic foundation models adapted from species‐level classifiers. However,
Jonathan Gallego, Juan D. Martinez‐Vargas, José D. López   +2 more
wiley   +1 more source

A modified U-Net convolutional neural network for segmenting periprostatic adipose tissue based on contour feature learning

Heliyon
Objective: This study trains a U-shaped fully convolutional neural network (U-Net) model based on peripheral contour measures to achieve rapid, accurate, automated identification and segmentation of periprostatic adipose tissue (PPAT). Methods: Currently,
Gang Wang, Jinyue Hu, Yu Zhang, Zhaolin Xiao, Mengxing Huang, Zhanping He, Jing Chen, Zhiming Bai   +7 more
doaj   +1 more source

Automated liver tumor segmentation and classification using AI and fully convolutional neural network (CNN) [PDF]

, 2021
The aim of this thesis is to design and implement automated liver tumor segmentation and classification using AI and fully convolutional neural network (FCNN). This represents more of a challenge when speaking of advance object recognition systems.
Dhahir, Idrees Ahmed Dhahir
core   +1 more source

Fully convolutional network for rice seedling and weed image segmentation at the seedling stage in paddy fields

PLoS ONE, 2019
To reduce the cost of production and the pollution of the environment that is due to the overapplication of herbicide in paddy fields, the location information of rice seedlings and weeds must be detected in site-specific weed management (SSWM). With the
Xu Ma, Xiang-Wu Deng, Long Qi, Yu Jiang, Hongwei Li, Yuwei Wang, Xupo Xing   +6 more
semanticscholar   +1 more source

Multi-Branch Fully Convolutional Network for Face Detection [PDF]

, 2017
Face detection is a fundamental problem in computer vision. It is still a challenging task in unconstrained conditions due to significant variations in scale, pose, expressions, and occlusion.
Bai, Yancheng, Ghanem, Bernard
core  

A method of multifeatured full convolutionalneural network based on speech enhancement in airground voice communication

四川大学学报. 自然科学版, 2020
In order to study speech enhancement in the air traffic control (ATC) and save storage resources, a new speech enhancement method is proposed. Based on Fully Convolutional Networks (FCN), Skip connection is added and secondary features are introduced for
Gao dengfeng, YangBo, YangHongyu, LiuHong   +3 more
doaj  

Inpatient Length of Stay and Mortality Prediction Utilizing Clinical Time Series Data

IEEE Access
Electronic Health Records (EHRs), which include demographic information, clinical notes, vital signs, laboratory test results, and others, provide rich information for clinical outcome prediction.
Junde Chen, Mason Li, Miles Milosevich, Tiffany Le, Andrew Bahsoun, Yuxin Wen   +5 more
doaj   +1 more source

Automatic Raft Labeling for Remote Sensing Images via Dual-Scale Homogeneous Convolutional Neural Network

Remote Sensing, 2018
Raft-culture is a way of utilizing water for farming aquatic product. Automatic raft-culture monitoring by remote sensing technique is an important way to control the crop’s growth and implement effective management.
Tianyang Shi, Qizhi Xu, Zhengxia Zou, Zhenwei Shi   +3 more
doaj   +1 more source

Fully Convolutional Networks for Multi-temporal SAR Image Classification [PDF]

, 2018
Classification of crop types from multi-temporal SAR data is a complex task because of the need to extract spatial and temporal features from images affected by speckle.
Tolpekin, V.A., Mullissa, A.G., Persello, C.   +2 more
core   +1 more source