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AI Battles the Bane of Space Junk

Flipboard

In a paper presented earlier this year at the European Space Agency’s second NEO and Debris Detection Conference in Darmstadt, Germany, Fabrizio Piergentili and colleagues presented results of their evolutionary “genetic” algorithm to monitor the rotational motion of space debris.

AI 179
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Faster R-CNNs

PyImageSearch

Home Table of Contents Faster R-CNNs Object Detection and Deep Learning Measuring Object Detector Performance From Where Do the Ground-Truth Examples Come? One of the most popular deep learning-based object detection algorithms is the family of R-CNN algorithms, originally introduced by Girshick et al.

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In-depth analysis of artificial intelligence techniques for emotion detection: State-of-the-art, approaches, and perspectives

Dataconomy

Machine learning models: Machine learning models, such as support vector machines, recurrent neural networks, and convolutional neural networks, are used to predict emotional states from the acoustic and prosodic features extracted from the voice. Deep learning techniques have particularly excelled in emotion detection from voice.

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Navigating tomorrow: Role of AI and ML in information technology

Dataconomy

This popularity is primarily due to the spread of big data and advancements in algorithms. Going back from the times when AI was merely associated with futuristic visions to today’s reality, where ML algorithms seamlessly navigate our daily lives. These technologies have undergone a profound evolution. billion by 2032.

ML 121
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16 Companies Leading the Way in AI and Data Science

ODSC - Open Data Science

Improving Operations and Infrastructure Taipy The inspiration for this open-source software for Python developers was the frustration felt by those who were trying, and struggling, to bring AI algorithms to end-users. Cloudera For Cloudera, it’s all about machine learning optimization.

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sktime?—?Python Toolbox for Machine Learning with Time Series

ODSC - Open Data Science

Build tuned auto-ML pipelines, with common interface to well-known libraries (scikit-learn, statsmodels, tsfresh, PyOD, fbprophet, and more!) We’re always looking for new algorithms to be hosted, these are owned by their author and maintained together with us. We welcome all forms of contributions, not just code. Something else?

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Crack Detection in Concrete

Towards AI

Basically crack is a visible entity and so image-based crack detection algorithms can be adapted for inspection. Deep learning algorithms can be applied to solving many challenging problems in image classification. Deep learning algorithms can be applied to solving many challenging problems in image classification.