A new, densely annotated 3D-text dataset called 3D-GRAND can help train embodied AI, like household robots, to connect ...

In the world of particle physics, where scientists unravel the mysteries of the universe, artificial intelligence (AI) and ...

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Abstract: In this paper, we explore the applicability of selected machine learning models to classify incoming ... Boosting with octets-transformed input data provides the best performance, reducing ...

Machine learning frameworks like Google’s TensorFlow ease the process of acquiring data, training models ... neural networks for handwritten digit classification, image recognition, word ...

Abstract: We present the Interactive Classification System (ICS), a web-based application that supports the activity of manual text ... of data. We satisfy the “total freedom” requirement by designing ...

Deep learning and machine ... FIGURE 3. Flowchart of the used methodology in the study. Biased Support vector machines, Random Forests, Convolutional Neural Networks, and their ensemble classification ...

Enterprise machine learning ... data iteration capabilities, and pre-built templates for classification of and information extraction from documents. Register for the first in a series of Snorkel ...

However, text sentiment analysis based on machine learning relies on sufficient labeled training data. Aiming at the problem of sentiment classification of news text data with insufficient label news ...