Artificial Neural Network Technology Continues to Unveil its Multidimensional Potential
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An artificial neural network is a form of artificial intelligence with a series of algorithms that recognize the relationship between the data sets. It imitates the human brain learning process to solve the complex pattern recognition problems, in particular to analyze large data sets. Some popular types of neural networks are autoencoders, convolutional neural networks, and recurrent neural networks. Neural networks are widely used for real-world business problems involving data validation, customer research, forecasting, and risk management. It is applied across various industries such as marketing, retail & sales, banking & finance, and medicine, among others.
Analytical Software to Demystify the Intricacies Involved in a Surveillance Video
The analytical software segment is projected to hold significant market share among other type segments in the global neural network software market on account of government organizations increasingly using surveillance systems for investigations. The recordings in the surveillance systems often have lower resolution, compelling law enforcement agencies to embrace advanced technological solutions to analyze video patterns. For instance, in January 2019, BrainChip Holdings announced a strategic partnership with SoftCryptum to sell BrainChip’s AI-powered video analytics solutions to government agencies in France, Belgium, and Switzerland.
Katana Lens — An AI-Powered Tool, to Bring Forth Decisiveness in Trading
The prevalence of artificial intelligence into the trading systems is propelling the demand for neural network software market in the BFSI industry. Automated trading systems allow computers to monitor and execute trades. For instance, in October 2018, ING launched Katana Lens, an AI tool, that assists investors in finding and comparing trade ideas. The Katana Lens is a web-based application that provides predictive analytics to bond investors for facilitating faster and sharper decisions. Such instances are attributed to influence the finance segment growth in the global neural network software market.