The application of digital cameras to monitor the environment is becoming global and
changing the way of phenological data collection. The technique of repeated digital …

In the field of fine-grained visual recognition (FGVR), the ability to resolve minute and often
subtle differences between highly similar object categories is paramount. The advent of …

Fine-grained grocery product recognition via camera is a challenging task to identify the
visually similar products with subtle differences by using single-shot training examples. To …

Pixelwise image classification based on time series profiles has been very effective in
several applications. In this letter, we investigate recently proposed image-based time series …

Nowadays, global warming and its resulting environmental changes is a hot topic in different
biology research area. Phenology is one effective way of tracking such environmental …

This article addresses the pixelwise classification problem based on temporal profiles, which
are encoded in 2-D representations based on recurrence plots, Gramian angular/difference …

This paper investigates the accuracy of five state-of-the-art machine learning techniques—
decision tree J48, nearest neighbors, k-nearest neighbors (k-NN), backpropagation neural …

In this paper, we analyse the use of convolutional neural networks (CNNs or ConvNets) to
discriminate vegetation species with few labelled samples. To the best of our knowledge …

Suitable time series representations play an important role in classification tasks. In this
letter, we investigate the use of recurrence-plot-(RP)-based representations in the …

Phenology is among the most trustworthy indicators of climate change effects on plants and
animals. The recent application of repeated digital photographs to monitor vegetation …