Summarization: DOG I (Dog OntoloGy Image annotator) is a complete and fully automated semantic annotation system for images of dog breeds. Annotation relies on feature extraction and on associating low-level features with image concepts in an ontology. Because general purpose ontologies for all image types are not yet available, we choose the problem of annotating images of dog breeds as a case study and for the evaluation of our methodology. Nevertheless, DOG I can be adapted to more image types provided that an ontology for a new image domain becomes available. Therefore, DOG I offers an ideal test-bed for experimentation and sets the grounds for the annotation and evaluation of virtually any image type. Evaluation results are realized us...
Oxford-IIIT Pet Dataset with ground truth labels for breeds (from https://public.roboflow.com/object...
Object recognition has become an extremely popular topic in today’s world as it is one of the core p...
The paper deals with an approach for a reliable dogface detection in an image using the convolutiona...
Abstract. DOGI (Dog OntoloGy Image annotator) is a complete and fully automated semantic annotation ...
Abstract In this paper, we introduce an image dataset for fine-grained classification of dog breeds:...
Abstract. We introduce SIA, a framework for annotating images auto-matically using ontologies. An on...
In this paper, we tackle the problem of visual categorization of dog breeds, which is a surprisingly...
Extracting and formulating an animal trait ontology is the basis of building a trait database. The c...
Our goal is to recover the 3D shape and pose of dogs from a single image. This is a challenging task...
<p>The gaze data were collected from five areas of interest (AOIs) of three facial expressions (Thre...
Estimating the pose of animals facilitates the understanding of animal motion and can permit the ear...
This image dataset has been derived from Wikimedia Commons (https://commons.wikimedia.org), a large-...
We introduce an automatic, end-to-end method for recovering the 3D pose and shape of dogs from monoc...
Preprocessed dataset for Tsinghua Dogs in YOLOv5 format.. Ground truth labels for head bounding box...
Image classification is one of the classical problems of Computer Vision, and with the advent of dee...
Oxford-IIIT Pet Dataset with ground truth labels for breeds (from https://public.roboflow.com/object...
Object recognition has become an extremely popular topic in today’s world as it is one of the core p...
The paper deals with an approach for a reliable dogface detection in an image using the convolutiona...
Abstract. DOGI (Dog OntoloGy Image annotator) is a complete and fully automated semantic annotation ...
Abstract In this paper, we introduce an image dataset for fine-grained classification of dog breeds:...
Abstract. We introduce SIA, a framework for annotating images auto-matically using ontologies. An on...
In this paper, we tackle the problem of visual categorization of dog breeds, which is a surprisingly...
Extracting and formulating an animal trait ontology is the basis of building a trait database. The c...
Our goal is to recover the 3D shape and pose of dogs from a single image. This is a challenging task...
<p>The gaze data were collected from five areas of interest (AOIs) of three facial expressions (Thre...
Estimating the pose of animals facilitates the understanding of animal motion and can permit the ear...
This image dataset has been derived from Wikimedia Commons (https://commons.wikimedia.org), a large-...
We introduce an automatic, end-to-end method for recovering the 3D pose and shape of dogs from monoc...
Preprocessed dataset for Tsinghua Dogs in YOLOv5 format.. Ground truth labels for head bounding box...
Image classification is one of the classical problems of Computer Vision, and with the advent of dee...
Oxford-IIIT Pet Dataset with ground truth labels for breeds (from https://public.roboflow.com/object...
Object recognition has become an extremely popular topic in today’s world as it is one of the core p...
The paper deals with an approach for a reliable dogface detection in an image using the convolutiona...