Computer Sciences

How severe are those software bugs?

The automated labeling and severity prediction of bug reports for computer software is the target of researchers at The Hashemite University in Zarqa, Jordan. Details of their efforts are mapped out in the International Journal ...

Computer Sciences

SPFCNN-Miner: A new classifier to tackle class-unbalanced data

Researchers at Chongqing University in China have recently developed a cost-sensitive meta-learning classifier that can be used when the training data available is high-dimensional or limited. Their classifier, called SPFCNN-Miner, ...

Machine Learning & AI

CruzAffect: a feature-rich approach to characterize happiness

A team of researchers at UC Santa Cruz have recently developed a new machine learning approach to characterize happiness, called CruzAffect. Their approach, presented in a paper pre-published on arXiv, can be applied to different ...

Computer Sciences

An AI that 'de-biases' algorithms

We've learned in recent years that AI systems can be unfair, which is dangerous, as they're increasingly being used to do everything from predicting crime to determining what news we consume. Last year's study showing the ...

Computer Sciences

A new approach for steganography among machine learning agents

Researchers at the University of Wisconsin-Madison and Amherst College have recently introduced a new form of steganography in the domain of machine learning called "training set camouflage." Their framework, outlined in ...

Computer Sciences

ColorUNet: A new deep CNN classification approach to colorization

A team of researchers at Stanford University has recently developed a CNN classification method to colorize grayscale images. The tool they devised, called ColorUNet, draws inspiration from U-Net, a fully convolutional network ...

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