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TerraQuanta has been selected as "101 Most Innovative Chinese Machine Learning Companies"

Artificial Intelligence driven by machine learning algorithms is infiltrating our lives in many ways and carrying great commercial value in many industries.
TerraQuanta has been selected as "101 Most Innovative Chinese Machine Learning Companies"

The development of the Internet has provided us easier ways to access to data, which brought us more breakthroughs on machine learning. Artificial Intelligence driven by machine learning algorithms is infiltrating our lives in many ways and carrying great commercial value in many industries.

In the context of the prosperous development of the global artificial intelligence industry,  theAmerican business magazines "Futurology Life" launched the "101 Most Innovative Chinese Machine Learning Companies". "Futurology Life" aims to explore the most creative and innovative companies in the industry through professional evaluation and analysis, and to promote these cutting-edge companies on a global scale.

"Futurology Life" comprehensively considered the concepts of innovative - innovative market paths, innovative products, growth strategies, management, and social impact of artificial intelligence companies of different sizes in China. The final list comprehensively included many well-known artificial intelligence companies such as Bytedance, SenseTime, and Megvii, and also includes TerraQuanta - a leading company in the field of spatial big data.

Machine learning is the core of artificial intelligence, and algorithms is the core of machine learning.

TerraQuanta self-developed Digital Earth PaaS cloud platform, which can automatically realize the entire process of remote sensing data from downloading to preprocessing. It not only ensures the efficient management and rapid update of the massive data in the background, but also effectively improves the efficiency of algorithm development that allows us to face the new challenges more easily.

On the basis of the PB-level data supercomputing center and locally built data processing system, TerraQuanta also has a number of independently innovative AI algorithms and forming an automated space-time deep learning platform. Based on this deployment that based on the most cutting-edge model in the machine learning industry can segment and classify multi-source remote sensing images with the characteristics of the three dimensions of spectrum, time and space, which can achieve efficient and accurate analysis of ground and air data in the national and even intercontinental ranges. It can help us to obtain high-value key data such as rapid assessment of flood damage in the middle and lower reaches of the Yangtze River, and statistics on soybean planting areas across the United States.

TerraQuanta widely applied its self-developed algorithms in product practice. At present, it has the world's leading techniques such as cultivated land identification, crop classification, disaster monitoring, and yield prediction with data accuracy. It is one of the few domestic platforms that are  capable of processing the global level by remote sensing.

The farmland segmentation technology based on deep learning can carry out high-precision vectorization of fields in any area in China, and can further circle and select any land for long-term monitoring of key indicators of crop growth, and respond to recent data and current conditions in minutes.

For flood disasters, TerraQuanta uses the time series backscattering information of SAR satellites to normalize and complete all-weather water area extraction in a large range. It can quickly discover the flooded area to determine the severity of the disaster, and it can also integrate its crops classification technology and calculating the situation of disaster of specific crops and so on.

The development of the remote sensing industry initially benefited from the needs of military reconnaissance. As governments gradually realized the huge commercial application value of the satellite industry, the new aerospace economy industry has been developed, and satellite remote sensing data is no longer difficult to reach.

Combined with machine learning and other technologies, the commercial value of remote sensing satellite data has been pushed to unprecedented new heights, allowing many government and civilian fields to use the ideas provided by spatial data to conceive new strategies, new products, and new services.