Recognition of queen loss state of honeycomb based on multi-domain feature fusion

No abstract is available for this paper.

• Publication year

  2025

• Venue

  Youth Academic Annual Conference of Chinese Association of Automation

• Publication date

  2025-05-17

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1109/YAC66630.2025.11150078
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• A deep learning-based approach for bee sound identification

  2023cited by this paper
• Applicability of VGGish embedding in bee colony monitoring: comparison with MFCC in colony sound classification

  2023cited by this paper
• Comparison of Feature Extraction Methods for Sound-Based Classification of Honey Bee Activity

  2022cited by this paper
• Honeybees swarming detection approach by sound signal processing

  2020cited by this paper
• Analysis of the Sound Emitted by Honey Bees in a Beehive

  2019cited by this paper
• Toward Audio Beehive Monitoring: Deep Learning vs. Standard Machine Learning in Classifying Beehive Audio Samples

  2018cited by this paper
• REMOTE BEEHIVE MONITORING USING ACOUSTIC SIGNALS

  2014cited by this paper
• Economic gain, stability of pollination and bee diversity decrease from southern to northern Europe

  2013cited by this paper
• Intracolony vibroacoustic communication in social insects

  2013cited by this paper
• Bee diversity effects on pollination depend on functional complementarity and niche shifts.

  2013cited by this paper
• Stability of pollination services decreases with isolation from natural areas despite honey bee visits.

  2011cited by this paper
• Importance of pollinators in changing landscapes for world crops

  2007cited by this paper

• No citing papers are available for this paper.