Results 91 to 100 of about 6,093,681 (207)

PancDS in Real‐World Practice: A Prospective Multicenter Validation of a Clinical Decision‐Support System Bridging Experience Gaps in Pancreatic Lesion Diagnosis

Advanced Science, Volume 13, Issue 45, 13 August 2026.
A biomimetic artificial intelligence system, PancDS, has been developed to distinguish pancreatic ductal adenocarcinoma from mass‐forming pancreatitis by adaptively integrating clinical data, radiomics, and deep learning features. Validated across multicenter, reader‐study, and prospective settings, PancDS improves diagnostic accuracy, particularly for
Zhibo Wang, Weinuo Qu, Wenwen Cai, Chuhuai Wang, Chenxi Lyu, Qingguo Xie, Qian Chu, Yaqi Shen, Peng Xiao, Feng Li, Qingpeng Zhang, Jiali Li, Jeong Min Lee, Zhen Li   +13 more
wiley   +1 more source

A Semantic Segmentation Algorithm Using FCN with Combination of BSLIC

Applied Sciences, 2018
An image semantic segmentation algorithm using fully convolutional network (FCN) integrated with the recently proposed simple linear iterative clustering (SLIC) that is based on boundary term (BSLIC) is developed.
Wei Zhao, Haodi Zhang, Yujin Yan, Yi Fu, Hai Wang   +4 more
doaj   +1 more source

A Novel Full‐Chain Loop Tracking Auditing Framework for Obtaining Audit Evidence With Reasonable Assurance

CAAI Transactions on Intelligence Technology, Volume 11, Issue 4, Page 1194-1214, August 2026.
ABSTRACT As an attestation engagement, auditing is required to provide reasonable assurance for its conclusions. Traditional auditing has limited capacity to handle unstructured data and is usually based on audit sampling techniques, which can lead to the neglect of important audit evidence during the auditing process and result in a higher audit risk,
Xiaojia Wang, Ziqing Luo, Chaoxu Mu
wiley   +1 more source

Asymmetric Encoder-Decoder Structured FCN Based LiDAR to Color Image Generation

Sensors, 2019
In this paper, we propose a method of generating a color image from light detection and ranging (LiDAR) 3D reflection intensity. The proposed method is composed of two steps: projection of LiDAR 3D reflection intensity into 2D intensity, and color image ...
Hyun-Koo Kim, Kook-Yeol Yoo, Ju H. Park, Ho-Youl Jung   +3 more
doaj   +1 more source

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

TMSA‐Net: Transformer‐Based Multi‐Scale Attention U‐Net for Flood Image Segmentation

CAAI Transactions on Intelligence Technology, Volume 11, Issue 4, Page 1104-1126, August 2026.
ABSTRACT Flood detection is essential for real‐time applications, including disaster management, emergency response, and alerting people in flood zones. For successful flood detection, accurate flood region segmentation is essential. However, the flood region segmentation is challenging due to the complex background and occlusions with debris and the ...
Parham Imanzadeh Charandabi, Shivakumara Palaiahnakote, Apostolos Antonacopoulos, Christian Clausner   +3 more
wiley   +1 more source

Insights Into LSTM Fully Convolutional Networks for Time Series Classification

IEEE Access, 2019
Long short-term memory fully convolutional neural networks (LSTM-FCNs) and Attention LSTM-FCN (ALSTM-FCN) have shown to achieve the state-of-the-art performance on the task of classifying time series signals on the old University of California-Riverside (
Fazle Karim, Somshubra Majumdar, Houshang Darabi   +2 more
doaj   +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

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  

Staircase detection using a lightweight look-behind fully convolutional neural network

, 2019
Staircase detection in natural images has several applications in the context of robotics and visually impaired navigation. Previous works are mainly based on handcrafted feature extraction and supervised learning using fully annotated images.
Diamantis D.E., Koutsiou D.-C.C., Iakovidis D.K.
core   +1 more source