[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Pegoraro et al., 2020 - Google Patents

Automated video monitoring of insect pollinators in the field

Pegoraro et al., 2020

View PDF
Document ID
5921114822798348448
Author
Pegoraro L
Hidalgo O
Leitch I
Pellicer J
Barlow S
Publication year
Publication venue
Emerging topics in life sciences

External Links

Snippet

Ecosystems are at increasing risk from the global pollination crisis. Gaining better knowledge about pollinators and their interactions with plants is an urgent need. However, conventional methods of manually recording pollinator activity in the field can be time-and …
Continue reading at www.researchgate.net (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/00771Recognising scenes under surveillance, e.g. with Markovian modelling of scene activity
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30244Information retrieval; Database structures therefor; File system structures therefor in image databases
    • G06F17/30247Information retrieval; Database structures therefor; File system structures therefor in image databases based on features automatically derived from the image data
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N5/00Details of television systems
    • H04N5/222Studio circuitry; Studio devices; Studio equipment; Cameras comprising an electronic image sensor, e.g. digital cameras, video cameras, TV cameras, video cameras, camcorders, webcams, camera modules for embedding in other devices, e.g. mobile phones, computers or vehicles
    • H04N5/225Television cameras; Cameras comprising an electronic image sensor, e.g. digital cameras, video cameras, video cameras, camcorders, webcams, camera modules for embedding in other devices, e.g. mobile phones, computers or vehicles
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis

Similar Documents

Publication Publication Date Title
Pegoraro et al. Automated video monitoring of insect pollinators in the field
Bjerge et al. Real‐time insect tracking and monitoring with computer vision and deep learning
Høye et al. Deep learning and computer vision will transform entomology
Bjerge et al. A computer vision system to monitor the infestation level of Varroa destructor in a honeybee colony
Steen Diel activity, frequency and visit duration of pollinators in focal plants: in situ automatic camera monitoring and data processing
Miranda et al. Pest detection and extraction using image processing techniques
Weinstein M otion M eerkat: integrating motion video detection and ecological monitoring
CN101918989B (en) Video surveillance system with object tracking and retrieval
Song et al. Detection of maize tassels for UAV remote sensing image with an improved YOLOX model
US11989936B2 (en) Leveraging smart-phone cameras and image processing techniques to classify mosquito genus and species
Sledevič The application of convolutional neural network for pollen bearing bee classification
Steen et al. Portable digital video surveillance system for monitoring flower-visiting bumblebees
Selby et al. Precise and low-cost monitoring of plum curculio (Coleoptera: Curculionidae) pest activity in pyramid traps with cameras
Haas-Stapleton et al. Assessing mosquito breeding sites and abundance using an unmanned aircraft
Nasir et al. AI in apiculture: a novel framework for recognition of invasive insects under unconstrained flying conditions for smart beehives
König IndusBee 4.0–integrated intelligent sensory systems for advanced bee hive instrumentation and hive keepers' assistance systems
Sun et al. A visual tracking system for honey bee (hymenoptera: Apidae) 3D flight trajectory reconstruction and analysis
Bilik et al. Machine learning and computer vision techniques in continuous beehive monitoring applications: A survey
Desell et al. Wildlife@ Home: Combining crowd sourcing and volunteer computing to analyze avian nesting video
Petrov et al. Computer vision technology in the development of an ultrasonic repeller
Rocha IV et al. Philippine carabao mango pest identification using convolutional neural network
DE102019131858A1 (en) System for the automatic detection and determination of moving objects
Bjerge et al. A deep learning pipeline for time-lapse camera monitoring of floral environments and insect populations
CN116189076A (en) Observation and identification system and method for bird observation station
Slim et al. Smart insect monitoring based on YOLOV5 case study: Mediterranean fruit fly Ceratitis capitata and Peach fruit fly Bactrocera zonata