A team of researchers at MIT CSAIL, in collaboration with Cornell University and Microsoft, have developed STEGO, an algorithm able to identify images down to the individual pixel.

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Computer vision algorithms usually rely on convolutional neural networks, or CNNs. CNNs typically use convolutional, pooling, ReLU, fully connected, and loss layers to simulate a visual cortex.

Driverless cars, for example, use computer vision and image recognition to identify pedestrians, signs, and other vehicles. For a deeper dive into computer vision check out the following: ...

Examples of computer vision in action include optical character recognition, image recognition, pattern recognition, facial recognition, and object detection and classification.

Doctors determine the size of the tumor lesions by manually marking 2D slice images – an extremely time-consuming task. “Automated evaluation using an algorithm would save an enormous amount of time ...

Artificial intelligence has the potential to improve the analysis of medical image data. For example, algorithms based on deep learning can determine the location and size of tumors. This is the ...