Human activities produce contaminants, the amounts and toxicity of which often exceed the environment’s homeostatic capacity to cleanse itself. Hence, the systematic analysis and monitoring of the environment is increasingly a matter of urgency. Honey bees, thanks to their morphological features, and also bee products are regarded as good indicators of environmental pollution by toxic substances, be these heavy metals, radioactive...

This work describes a bee detection system to monitor bee colony conditions. The detection process on video images has been divided into 3 stages: determining the regions of interest (ROI) for a given frame, scanning the frame in ROI areas using the DNN-CNN classifier, in order to obtain a confidence of bee occurrence in each window in any position and any scale, and form one detection window from a cloud of windows provided by...

This paper presents an approach to bee detection in video streams using a neural network classifier. We describe the motivation for our research and the methodology of data acquisition. The main contribution to this work is a comparison of different color models used as an input format for a feedforward convolutional architecture applied to bee detection. The detection process has is based on a neural binary classifier that classifies...