Related papers: GalliformeSpectra: A Hen Breed Dataset
We present the Pascal animal classes Eye Tracking database. Our database comprises eye movement recordings compiled from forty users for the bird, cat, cow, dog, horse and sheep {trainval} sets from the VOC 2012 image set. Different from…
Discovering genes with similar functions across diverse biomedical contexts poses a significant challenge in gene representation learning due to data heterogeneity. In this study, we resolve this problem by introducing a novel model called…
Herbaria worldwide are housing a treasure of 100s of millions of herbarium specimens, which are increasingly being digitized in recent years and thereby made more easily accessible to the scientific community. At the same time, deep…
Synthesizing medical images, such as PET, is a challenging task due to the fact that the intensity range is much wider and denser than those in photographs and digital renderings and are often heavily biased toward zero. Above all,…
Recent work has established the ecological importance of developing algorithms for identifying animals individually from images. Typically, a separate algorithm is trained for each species, a natural step but one that creates significant…
Accurate phenotypic analysis in aquaculture breeding necessitates the quantification of subtle morphological phenotypes. Existing datasets suffer from limitations such as small scale, limited species coverage, and inadequate annotation of…
Automated plant identification has improved considerably thanks to recent advances in deep learning and the availability of training data with more and more field photos. However, this profusion of data concerns only a few tens of thousands…
Cattle face recognition holds paramount significance in domains such as animal husbandry and behavioral research. Despite significant progress in confined environments, applying these accomplishments in wild settings remains challenging.…
The development of foundation vision models has pushed the general visual recognition to a high level, but cannot well address the fine-grained recognition in specialized domain such as invasive species classification. Identifying and…
Technology-driven precision livestock farming (PLF) empowers practitioners to monitor and analyze animal growth and health conditions for improved productivity and welfare. Computer vision (CV) is indispensable in PLF by using cameras and…
Because of their close relationship with humans, non-human apes (chimpanzees, bonobos, gorillas, orangutans, and gibbons, including siamangs) are of great scientific interest. The goal of understanding their complex behavior would be…
Since the advent of controllable image generation, increasingly rich modes of control have enabled greater customization and accessibility for everyday users. Zero-shot, identity-preserving models such as Insert Anything and OminiControl…
Entomologists, ecologists and others struggle to rapidly and accurately identify the species of bumble bees they encounter in their field work and research. The current process requires the bees to be mounted, then physically shipped to a…
More than 1000 complete or near-complete mitochondrial DNA (mtDNA) sequences have been deposited in GenBank for eight common domestic animals (i.e. cattle, dog, goat, horse, pig, sheep, yak and chicken) and their close wild ancestors or…
The performance of unified multimodal models for image generation and editing is fundamentally constrained by the quality and comprehensiveness of their training data. While existing datasets have covered basic tasks like style transfer and…
We present the first unsupervised deep learning method for pollen analysis using bright-field microscopy. Using a modest dataset of 650 images of pollen grains collected from honey, we achieve family level identification of pollen. We embed…
Spatial transcriptomics (ST) measures gene expression at fine-grained spatial resolution, offering insights into tissue molecular landscapes. Previous methods for spatial gene expression prediction typically crop spots of interest from…
Wheat is one of the most significant crop species with an annual worldwide grain production of 700 million tonnes. Assessing the production of wheat spikes can help us measure the grain production. Thus, detecting and characterizing spikes…
The aim of this paper was to develop statistical models to estimate individual breed composition based on the previously proposed idea of regressing discrete random variables corresponding to counts of reference alleles of biallelic…
This study revisits the findings of Carl et al., who evaluated the pre-trained Google Inception-ResNet-v2 model for automated detection of European wild mammal species in camera trap images. To assess the reproducibility and…