Pre-processing might include a complex sequence of steps, starting with turning the image to grayscale. Thresholding, blurring, edge detection, line and shape detection, and more adjustments might ...

The recognition pattern however is broader than just image recognition In fact, we can use machine learning to recognize and understand images, sound, handwriting, items, face, and gestures.

Other companies have been as interested in the idea of deep learning, with Google hiring noted immortalist Ray Kurzweil to develop an artificial brain. The company has also invested in image ...

Many machine learning problems fall into one of three categories: tabular data prediction (such as the Iris species problem), natural language processing (such as the IMDB movie review sentiment ...

Training material: Open data. Thanks to deep learning techniques, a machine learning technique loosely modeled after the human brain, computers can be taught to accurately identify what’s in ...

After 10 years of ImageNet, AI researchers are digging into the details of test sets and some are asking just how much knowledge has really been created with machine learning.

Our understanding of progress in machine learning has been colored by flawed testing data. The 10 most cited AI data sets are riddled with label errors, according to a new study out of MIT, and it ...

High Accuracy: Deep learning models can achieve state-of-the-art performance on many tasks, often surpassing human-level accuracy in areas like image recognition and language understanding.