Suchergebnisse - "Computer vision algorithm"

distect: automatic sample-position tracking for X-ray experiments using computer vision algorithms

Autoren: Michael Berg Dirk Furrer Vincent Thominet et al.

Quelle: J Synchrotron Radiat
Journal of Synchrotron Radiation, Vol 31, Iss 6, Pp 1514-1524 (2024)

Schlagwörter: sample-position tracking, Crystallography, soft x-ray absorption spectroscopy, computer vision algorithms, QC770-798, 006: Spezielle Computerverfahren, Computer vision algorithm, Research Papers, Sample-position accuracy, 540: Chemie, Sample-position tracking, Soft X-ray absorption spectroscopy, QD901-999, Nuclear and particle physics. Atomic energy. Radioactivity, sample-position accuracy, variable temperature inserts, Variable temperature inserts

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/39475837
https://doaj.org/article/0cd18cbca48e452f8aa6b7ad872433af

Technological Innovations in Agriculture for Scouting Halyomorpha Halys in Orchards

Autoren: Almstedt, Lennart Baltieri, Davide Betti Sorbelli, Francesco et al.

Quelle: 2023 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT). :702-709

Schlagwörter: Automatic monitoring, Canopy's micro-climate station, Computer Vision Algorithm, Halyomorpha halys detection, Hardware Evaluation, IoT trap, Technological transfer, Halyomorpha halys detection, Automatic monitoring, Hardware Evaluation, Computer Vision Algorithm, Technological transfer, IoT trap, Canopy's micro-climate station, Deep learning, Training, Economics, Technological innovation, Image edge detection, Autonomous aerial vehicles, Hardware

Dateibeschreibung: application/pdf

A Drone-based Automated Halyomorpha halys Scouting: A Case Study on Orchard Monitoring

Autoren: Betti Sorbelli, Francesco Palazzetti, Lorenzo Pinotti, Cristina M.

Quelle: 2023 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor). :380-385

Schlagwörter: Halyomorpha halys detection, Drones, Computer Vision Algorithm, Technological transfer

Dateibeschreibung: application/pdf

Zugangs-URL: https://ieeexplore.ieee.org/document/10424287
https://hdl.handle.net/11391/1568534
https://doi.org/10.1109/MetroAgriFor58484.2023.10424287

Preliminary Results for Halyomorpha halys Monitoring Relying on a Custom Dataset

Autoren: Betti Sorbelli, Francesco Palazzetti, Lorenzo Pinotti, Cristina M.

Quelle: 2023 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor). :363-368

Schlagwörter: Halyomorpha halys detection, Drones, Computer Vision Algorithm, Technological transfer

Dateibeschreibung: application/pdf

Zugangs-URL: https://hdl.handle.net/11391/1568533
https://doi.org/10.1109/MetroAgriFor58484.2023.10424403
https://ieeexplore.ieee.org/document/10424403

RESOURCE-AWARE FACIAL RECOGNITION: A HYBRID CLOUD-EDGE COMPUTING APPROACH FOR LOW-END DEVICES

Autoren: Researcher

Schlagwörter: Facial Recognition Optimization, Resource-Constrained Computing, Edge-Cloud Computing, Mobile Computer Vision, Algorithm Efficiency

Automation of Construction and Demolition Waste Handling

Autoren: Diani Sirimewan

Schlagwörter: Construction engineering, MonashVYT, Construction waste management, Construction and Demolition Waste, Construction and demolition waste (C&D waste), construction and demolition debris, Construction and Demolition Waste (CDW), waste handling, waste handling processes, Automation, Automated waste handling, Automated waste recognition, Automated waste sorting, Computer vision, computer vision algorithm, artificial intelligence, Artificial Intelligence (AI), Construction and demolition waste handling, Construction and demolition waste sorting, Construction and demolition waste recognition

Relation: https://figshare.com/articles/presentation/Automation_of_Construction_and_Demolition_Waste_Handling/26074855

Verfügbarkeit: https://doi.org/10.26180/26074855.v1
https://figshare.com/articles/presentation/Automation_of_Construction_and_Demolition_Waste_Handling/26074855

Enhancing privacy with optical element design for fall detection

Autoren: Liyun Gong Sheldon Mccall Miao Yu

Quelle: Electronics Letters, Vol 59, Iss 20, Pp n/a-n/a (2023)

Schlagwörter: I460 - Machine learning, I100 - Computer science, deep learning, 02 engineering and technology, privacy preserving, health care, computer vision, TK1-9971, fall detection, machine learning, I440 - Computer vision, I400 - Artificial intelligence, 0202 electrical engineering, electronic engineering, information engineering, Fall Detection, computer vision algorithm, Electrical engineering. Electronics. Nuclear engineering

Zugangs-URL: https://doaj.org/article/c2dd0c89753e4152a3d925637ae31b3d

Eye-tracking glasses in face-to-face interactions: Manual versus automated assessment of areas-of-interest

Autoren: Jongerius, Chiara Callemein, T. Goedemé, T. et al.

Quelle: Behav Res Methods

Schlagwörter: Eye Movements, 05 social sciences, Reproducibility of Results, 02 engineering and technology, Computer vision algorithm, Article, 3. Good health, Eye-tracking glasses, Person re-identification, 0202 electrical engineering, electronic engineering, information engineering, Gaze behaviour, Humans, Areas-of-interest, 0501 psychology and cognitive sciences, Eye-Tracking Technology, Pose estimation, Algorithms, Vision, Ocular

Zugangs-URL: https://link.springer.com/content/pdf/10.3758/s13428-021-01544-2.pdf
https://pubmed.ncbi.nlm.nih.gov/33742418
https://link.springer.com/content/pdf/10.3758/s13428-021-01544-2.pdf
https://pubmed.ncbi.nlm.nih.gov/33742418/
https://www.ncbi.nlm.nih.gov/pubmed/33742418
https://link.springer.com/article/10.3758/s13428-021-01544-2
https://europepmc.org/article/PMC/PMC8516759
https://pure.amsterdamumc.nl/en/publications/4ebc5157-5301-4e2d-aad2-7649990fc635
https://doi.org/10.3758/s13428-021-01544-2

The hawk eye scan: Halyomorpha halys detection relying on aerial tele photos and neural networks

Autoren: Palazzetti, Lorenzo Rangarajan, Aravind Krishnaswamy Dinca, Alexandru et al.

Quelle: Computers and Electronics in Agriculture. 226:109365

Schlagwörter: Halyomorpha halys detection, Drones, Computer vision algorithm, Technological transfer

Zugangs-URL: https://hdl.handle.net/11391/1588380
https://doi.org/10.1016/j.compag.2024.109365
https://www.sciencedirect.com/science/article/pii/S0168169924007567

Application and Analysis of Computer Vision Algorithms in Graphics and Image Processing

Autoren: Zhou, Xiangming

Quelle: International Journal of Informatics and Information Systems; Vol 6, No 1: January 2023; 8 - 15 ; 2579-7069 ; 10.47738/ijiis.v6i1

Schlagwörter: Computer Vision Algorithm, Drone, Graphics and Image Processing, Real-time System

Dateibeschreibung: application/pdf

Relation: http://ijiis.org/index.php/IJIIS/article/view/149/104; http://ijiis.org/index.php/IJIIS/article/view/149

Verfügbarkeit: http://ijiis.org/index.php/IJIIS/article/view/149
https://doi.org/10.47738/ijiis.v6i1.149

Numerical analysis of mechanical properties at the internal interface of SFP material using a digital image algorithm

Autoren: Xiaoyu Liu Kuanghuai Wu Giovanni Giacomello et al.

Weitere Verfasser: Xiaoyu Liu Kuanghuai Wu Giovanni Giacomello et al.

Schlagwörter: Semi-flexible pavements (SFP), Finite element model, Composite interface, Computer vision algorithm, Digital image

Dateibeschreibung: ELETTRONICO

Relation: info:eu-repo/semantics/altIdentifier/wos/WOS:001400883000002; volume:58; issue:43; firstpage:1; lastpage:15; numberofpages:15; journal:MATERIALS AND STRUCTURES; https://hdl.handle.net/11577/3546296

Verfügbarkeit: https://hdl.handle.net/11577/3546296
https://doi.org/10.1617/s11527-025-02575-3
https://link.springer.com/article/10.1617/s11527-025-02575-3

Residual Transfer Learning for Multiple Object Tracking

Autoren: Gonzales Zuniga, Juan Diego Nguyen, Thi-Lan-Anh Bremond, Francois

Weitere Verfasser: Gonzales Zuniga, Juan Diego Nguyen, Thi-Lan-Anh Bremond, Francois

Quelle: 2018 15th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS). :1-6

Schlagwörter: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, Object tracking, [INFO] Computer Science [cs], Computer vision algorithm

Dateibeschreibung: application/pdf

Zugangs-URL: https://hal.inria.fr/hal-01928612/file/PID5568623.pdf
https://inria.hal.science/hal-01928612v1
https://hal.inria.fr/hal-01928612
https://hal.inria.fr/hal-01928612/document
https://dblp.uni-trier.de/db/conf/avss/avss2018.html#ZunigaNB18
http://dblp.uni-trier.de/db/conf/avss/avss2018.html#ZunigaNB18

Exploring data-efficient multi-modal learning in computer vision

Autoren: Linglin Jing

Schlagwörter: Computer vision algorithm

Verfügbarkeit: https://doi.org/10.26174/thesis.lboro.28944089.v1
https://figshare.com/articles/thesis/Exploring_data-efficient_multi-modal_learning_in_computer_vision/28944089

Simultaneous semantic segmentation and friction estimation using hierarchical latent variable models

Autoren: Mohammad Otoofi

Schlagwörter: Deep learning, Computer vision algorithm, Semantic segmentation, Friction coefficients, Regression algorithm, Variational autoencoder (VAE), Probabalistic neural networks, Generative AI (GenAI), Uncertainty analysis, Vehicle

Relation: https://figshare.com/articles/thesis/Simultaneous_semantic_segmentation_and_friction_estimation_using_hierarchical_latent_variable_models/28352609

Verfügbarkeit: https://doi.org/10.26174/thesis.lboro.28352609.v1
https://figshare.com/articles/thesis/Simultaneous_semantic_segmentation_and_friction_estimation_using_hierarchical_latent_variable_models/28352609

Analyse d'images pour le suivi d'animaux d'élevage

Autoren: Bonneau, Mathieu Canario, Laurianne, L. Labrune, Yann et al.

Weitere Verfasser: Bonneau, Mathieu Canario, Laurianne, L. Labrune, Yann et al.

Quelle: GDR ISIS - Intelligence artificielle/Apprentissage machine pour l'agriculture ; https://hal.inrae.fr/hal-03023955 ; GDR ISIS - Intelligence artificielle/Apprentissage machine pour l'agriculture, Centre national de la recherche scientifique, Nov 2020, Inconnu, France

Schlagwörter: Monitoring, Computer vision algorithm, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]

Geographisches Schlagwort: Inconnu, France

Verfügbarkeit: https://hal.inrae.fr/hal-03023955
https://hal.inrae.fr/hal-03023955v1/document
https://hal.inrae.fr/hal-03023955v1/file/IA_Agriculture_WebConf_V2.pdf

Computer vision algorithm to extract color data of pixels in microfluidic paper based analytical devices

Autoren: Deotale, Saurabh, author Beveridge, James Ross, advisor Blanchard, Nathaniel, committee member et al.

Schlagwörter: data extraction, region growing, microfludic paper-based devices, computer vision algorithm

Dateibeschreibung: born digital; masters theses; application/pdf

Relation: 2020-; Deotale_colostate_0053N_16595.pdf; https://hdl.handle.net/10217/233675

Verfügbarkeit: https://hdl.handle.net/10217/233675

Innovate Spatial-Temporal Attention Network (STAN) for Accurate 3D Mice Pose Estimation with a Single Monocular RGB Camera

Autoren: Liyun Gong Miao Yu Gautam Siddharth Kashyap et al.

Schlagwörter: I400 - Artificial intelligence, I440 - Computer vision, I460 - Machine learning, deep learning, pose estimation, computer vision algorithm

Relation: 10779/lincoln.28105586.v1

Verfügbarkeit: https://figshare.com/articles/conference_contribution/Innovate_Spatial-Temporal_Attention_Network_STAN_for_Accurate_3D_Mice_Pose_Estimation_with_a_Single_Monocular_RGB_Camera/28105586

Estimates of plant density of wheat crops at emergence from very low altitude UAV imagery

Autoren: Jin, Xiuliang Liu, Shouyang Baret, Frederic et al.

Weitere Verfasser: Jin, Xiuliang Liu, Shouyang Baret, Frederic et al.

Quelle: Remote Sensing of Environment (198), 105-114. (2017)

Schlagwörter: biodiversité végétale, multi-objective particle swarm optimization (mopso), [SDE.MCG]Environmental Sciences/Global Changes, culture agricole, Plant density, Unmanned aerial vehicle, Computer vision algorithm, Particle swarm optimization (PSO)-support vector machine (SVM), Winter wheat, optimisation multi-objectifs par essaim particulaire (mopso), 04 agricultural and veterinary sciences, drone, [SDE.MCG] Environmental Sciences/Global Changes, blé, wheat, phénotypage, densité de végétation, 0401 agriculture, forestry, and fisheries, imagerie haute resolution, Milieux et Changements globaux

Dateibeschreibung: application/pdf

Zugangs-URL: https://hal.archives-ouvertes.fr/hal-01578842/file/harnessing_1.pdf
http://www.sciencedirect.com/science/article/pii/S0034425717302651
http://ui.adsabs.harvard.edu/abs/2017RSEnv.198..105J/abstract
https://www.cabdirect.org/cabdirect/abstract/20173268437
https://www.sciencedirect.com/science/article/pii/S0034425717302651
http://prodinra.inra.fr/record/404919
https://hal.science/hal-01578842v1/document
https://hal.science/hal-01578842v1
https://doi.org/10.1016/j.rse.2017.06.007

Context-Aware Surface Defect Detection in Reflective Objects

Autoren: Jorge Vasquez Albornoz

Schlagwörter: Mechanical engineering not elsewhere classified, computer vision algorithm, data centric ai, data Science, deep learning, Machine Learning, robotics, Mechanical Engineering

Verfügbarkeit: https://doi.org/10.1184/r1/27110749.v1
https://figshare.com/articles/thesis/Context-Aware_Surface_Defect_Detection_in_Reflective_Objects/27110749

Designing simple indoor navigation system for UAVs

Autoren: Kara-Mohamed, Mohamed Patra, Sourav Lanzon, Alexander

Quelle: Kara Mohamed, M, Patra, S & Lanzon, A 2011, Designing simple indoor navigation system for UAVs. in 2011 19th Mediterranean Conference on Control and Automation, MED 2011|Mediterr. Conf. Control Autom., MED. pp. 1223-1228, 2011 19th Mediterranean Conference on Control and Automation, MED 2011, Corfu, 1/07/11. https://doi.org/10.1109/MED.2011.5983054

Schlagwörter: 0209 industrial biotechnology, heavy image processing algorithm, indoor UAV, 02 engineering and technology, laser dots, Global Positioning System, aircraft navigation, cameras, 0202 electrical engineering, electronic engineering, information engineering, computer vision algorithm, indoor navigation system design, path planning, video shot quality, Nonvolatile memory, Earth, Random access memory, Cameras, Ferroelectric films, robot vision, aircraft control, laser beam, INS-GPS navigation system, CAH10-01-08 - electrical and electronic engineering, remotely operated vehicles, GPS signal, vision camera

Dateibeschreibung: application/pdf; text

Zugangs-URL: http://www.open-access.bcu.ac.uk/3929/1/2.pdf
https://research.manchester.ac.uk/en/publications/60bce480-55bb-42f5-b30a-17e947017b33
https://doi.org/10.1109/MED.2011.5983054
https://ieeexplore.ieee.org/document/5983054/
https://www.research.manchester.ac.uk/portal/files/33715778/FULL_TEXT.PDF
https://www.research.manchester.ac.uk/portal/en/publications/designing-simple-indoor-navigation-system-for-uavs(60bce480-55bb-42f5-b30a-17e947017b33).html
https://www.open-access.bcu.ac.uk/3929/
http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.ieee-000005983054
https://research.manchester.ac.uk/en/publications/60bce480-55bb-42f5-b30a-17e947017b33
https://doi.org/10.1109/MED.2011.5983054
https://pure.manchester.ac.uk/ws/files/33715778/FULL_TEXT.PDF