1, big data technology
Big data, IT industry terminology, refers to a collection of data that cannot be captured, managed and processed by conventional software tools within a certain time range. It is a massive, high-growth and diversified information asset, which needs a new processing mode to have stronger decision-making power, insight and discovery ability and process optimization ability.
2. Image recognition technology
Image recognition is a technology that computers process, analyze and understand images to identify different patterns of targets and objects. The recognition process includes image preprocessing, image segmentation, feature extraction and matching judgment. Simply put, image recognition is how a computer reads the contents of a picture like a human.
3. Handwriting recognition technology
Handwriting recognition can be divided into off-line handwriting recognition and on-line handwriting recognition due to different data acquisition methods. Handwritten characters processed by online handwriting recognition are the writing signals obtained by the writer through physical devices (such as digital pen, digital handwriting board or touch screen), and the writing trajectory is immediately input into the computer through regular sampling. Handwritten characters processed by off-line handwritten character recognition are two-dimensional pictures of handwritten characters collected by image acquisition equipment such as scanners or cameras.
4. Deep learning technology
Deep learning is a new field based on machine learning. It is a series of new algorithms, which originated from the neural network algorithm inspired by the human brain structure, and developed with the increase of the depth of the model structure, accompanied by the improvement of big data and computing power. The concept of deep learning was put forward by the famous scientist Geoffrey Hinton and others in the articles published in Science in 2006 and 2007.
Deep learning is currently applied to image processing and computer vision, natural language processing and speech recognition. Since 2006, the research and application of deep learning in the cooperation between academia and industry has made a breakthrough in the above fields. Taking the object recognition competition in classic images based on ImageNet as an example, it beats all traditional algorithms and achieves unprecedented accuracy.