Results 91 to 100 of about 1,313 (183)
To enhance land use/cover change (LUCC) simulation accuracy, we introduced ViViT-ANN-CA, blending video vision transformer’s spatio-temporal features extraction ability, artificial neural network‘s (ANN) non-linearity computing ability, and CA’s spatial ...
Yifan Gao (2344960) +4 more
core +1 more source
A Lightweight-Transformer-Enhanced 3DCNN Network for Wetland Mapping With Time-Series Imagery
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingDue to the high spectral similarity among wetland vegetation types, their uneven spatial distribution, and irregular object boundaries, wetland remote sensing monitoring faces significant challenges.
Hui Sheng +5 more
doaj +1 more source
IET Radar, Sonar &Navigation, Volume 19, Issue 1, January/December 2025.The model aims to tackle the forgeries observed in manipulated images. A dual‐stream contrastive learning network (DSCL‐Net) that jointly exploits spatial (pixel‐level) and frequency (noise‐level) cues was developed. ABSTRACT Image forgery detection aims to identify tampered content and localise manipulated regions within images.
Maryam Munawar, Mourad Oussalah
wiley +1 more source
, 2023 У роботі було застосовано метод 3DCNN для обробки тривимірних даних, які були отримані з інфрачервоної камери TrueDepth камери смартфону компанії Apple. Перевагою використання цієї технології є безмаркерна система.
Андрущенко, М. А.
core
VidFormer: A novel end-to-end framework fused by 3DCNN and Transformer for Video-based Remote Physiological Measurement [PDF]
Remote physiological signal measurement based on facial videos, also known as remote photoplethysmography (rPPG), involves predicting changes in facial vascular blood flow from facial videos.
Guo, Shisheng +5 more
core +1 more source
Contactless Health Monitoring: An Overview of Video‐Based Techniques Utilising Machine/Deep Learning
IET Wireless Sensor Systems, Volume 15, Issue 1, January/December 2025.This review article presents a comprehensive examination of contactless health monitoring techniques utilising machine learning (ML) and deep learning (DL) algorithms for the assessment of critical vital signs. ABSTRACT Vital signs are crucial indicators of an individual's physiological well‐being and represent one of the primary evaluations conducted ...
Alaa Hajr +3 more
wiley +1 more source
Fault diagnosis of industrial process using attention mechanism with 3DCNN-LSTM
Although architectures such as recurrent neural networks (RNN) perform well in time series prediction, there is still challenges for existing deep learning methods in extracting comprehensive spatio-temporal features.
Zhang, Ridong +2 more
core +1 more source
Recognition of facial emotion based on SOAR model
Frontiers in NeuroscienceIntroductionExpressing emotions play a special role in daily communication, and one of the most essential methods in detecting emotions is to detect facial emotional states.
Matin Ramzani Shahrestani +2 more
doaj +1 more source
Rapid maize seed vigor classification using deep learning and hyperspectral imaging techniques
Smart Agricultural TechnologyUtilizing conventional methods to assess the seed quality is typically destructive and time-consuming. This research aimed to develop a robust and efficient framework for classifying maize seed vigor using hyperspectral imaging and deep learning.
Papis Wongchaisuwat +4 more
doaj +1 more source
, 2022 Recoil-imaging gaseous time projection chambers (TPCs) with directional sensitivity are attractive for dark matter (DM) searches. Detectors capable of reconstructing 3D nuclear recoil directions would be uniquely sensitive to the predicted dipole angular
Sadowski, P. +4 more
core