Brilhador, A., Colonhezi, T.P., Bugatti, P.H., Lopes, F.M.: Combining texture and shape descriptors for bioimages classification: a case of study in ImageCLEF dataset. In: Ruiz-Shulcloper, J., Sanniti di Baja, G. (eds.) CIARP 2013, Part I. LNCS, vol. 8258, pp. 431–438....
Dataset compiled for the ImageCLEF 2016 Handwritten Scanned Document Retrieval challenge. It is derived from a subset of pages from unpublished manuscripts written by the philosopher and reformer, Jeremy Bentham, that have been digitised and transcribed under the Transcribe Bentham project [Causer 2012]...
Deployment of model to classify images from the ImageCLEF 2015 dataset - GitHub - Atharva-Gundawar/ImageCLEF: Deployment of model to classify images from the ImageCLEF 2015 dataset
In this section, we describe the dataset, metrics, models, fine-tuning strategy, image pre-processing, and text formatting. 3.1 Task Description and Dataset For ImageCLEFmed Caption 2021, participants were tasked with developing a system that could generate a caption for a given medical image. ...
(ROCOv2) dataset. For concept detection, multi-label predictions are compared against UMLS terms extracted from the original captions with additional manually curated concepts via the F1-score. For caption prediction, the semantic similarity of the predictions to the original captions...
Images for both tasks are part of the Radiology Objects in COntext version 2 (ROCOv2) dataset. For concept detection, multi-label predictions are compared against UMLS terms extracted from the original captions with additional manually curated concepts via the F1-score. For capti...
For ImageCLEF 2022, an extended version of the ImageCLEF 2020 dataset is used To reduce the scope and size of concepts, several concept extraction tools are analyzed prior to caption pre-processing methods. Concepts with less occurrence will be removed ...
Hence, an interactive watershed-based approach is applied to build the proposed method that is evaluated on the imageCLEFlifelog 2019 dataset and compared to participants joined this event. The experimental results confirm the high ... DT Dang-Nguyen,L Piras,M Riegler,... - Cross-language Evalu...
Convolutional neural networks have achieved state-of-theart results in general image classification tasks and have shown success in several applications within the medical imaging domain. In this paper, we apply a 3D convolutional neural network (CNN) to a dataset of tuberculosis-positive computed tom...
(s) when the lifelogger was having a beer on the beach with his/her friends”. Particular attention will be paid to the diversification of the selected moments with respect to the target scenario. To make the task possible and interesting a rich multimodal dataset will be used. The data ...