Deep Learning

Detecting radioactive materials in mixtures is challenging due to low concentration, environmental factors, sensor noise, and others. This paper presents new results on nuclear material identification and mixing ratio estimation for mixtures of materials in which there are multiple isotopes present. Conventional and deep learning-based machine learning algorithms were compared. Both simulated and actual experimental data were used in the comparative studies.

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Aspect Sentiment Triplet Extraction (ASTE) is an Aspect-Based Sentiment Analysis subtask (ABSA). It aims to extract aspect-opinion pairs from a sentence and identify the sentiment polarity associated with them. For instance, given the sentence ``Large rooms and great breakfast", ASTE outputs the triplet T = {(rooms, large, positive), (breakfast, great, positive)}. Although several approaches to ASBA have recently been proposed, those for Portuguese have been mostly limited to extracting only aspects without addressing ASTE tasks.

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199 Views

The University of Turin (UniTO) released the open-access dataset Stoke collected for the homonymous Use Case 3 in the DeepHealth project (https://deephealth-project.eu/). UniToBrain is a dataset of Computed Tomography (CT) perfusion images (CTP).

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842 Views

The lack of gold standard methodology for synergy quantification of anticancer drugs warrants the consideration of different synergy metrics to develop efficient Artificial Intelligence-based predictive methods. Furthermore, neglecting combination sensitivity in synergy prediction may lead to biased synergistic combinations that are inefficient in conferring anticancer activity.

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293 Views

The accompanying dataset for the CVSports 2021 paper: DeepDarts: Modeling Keypoints as Objects for Automatic Scoring in Darts using a Single Camera

Paper Abstract:

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The dermoscopic images considered in the paper "Dermoscopic Image Classification with Neural Style Transfer" are available for public download through the ISIC database (https://www.isic-archive.com/#!/topWithHeader/wideContentTop/main). These are 24-bit JPEG images with a typical resolution of 768 × 512 pixels. However, not all the images in the database are in satisfactory condition.

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779 Views

The Objects Mosaic Hyperspectral Database contains 10,666 hyperspectral cubes of size 256x256x29 in the 420-700nm spectral range. This original hyperspectral database of real objects was experimentally acquired as described in the paper "SHS-GAN: Synthetic enhancement of a natural hyperspectral database", by J. Hauser, G. Shtendel, A. Zeligman, A. Averbuch, and M. Nathan, in the IEEE Transactions on Computational Imaging.

In addition, the database contains the SHS-GAN algorithm, which enables to generate synthetic database of hyperspectral images. 

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Arbitrarily falling dices were photographed individually and monochromatically inside an Ulbricht sphere from two fixed perspectives. Overall, 11 dices with edge size 16 mm were used for 2133 falling experiments repeatedly. 5 of these dices were modified manually to have the following anomalies: drilled holes, missing dots, sawing gaps and scratches. All pictures in the uploaded pickle containers have a resolution of 400 times 400 pixels with normalized grey scale floating point values of 0 (black) through 1 (white).

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163 Views

Of late, efforts are underway to build computer-assisted diagnostic tools for cancer diagnosis via image processing. Such computer-assisted tools require capturing of images, stain color normalization of images, segmentation of cells of interest, and classification to count malignant versus healthy cells. This dataset is positioned towards robust segmentation of cells which is the first stage to build such a tool for plasma cell cancer, namely, Multiple Myeloma (MM), which is a type of blood cancer. The images are provided after stain color normalization.

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2808 Views

A fundamental building block of any computer-assisted interventions (CAI) is the ability to automatically understand what the surgeons are performing throughout the surgery. In other words, recognizing the surgical activities being performed or the tools being used by the surgeon can be deemed as an essential steps toward CAI. The main motivation for these tasks is to design efficient solutions for surgical workflow analysis. The CATARACTS dataset was proposed in this context. This dataset consists of 50 cataract surgery.

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3043 Views

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