AI Voucher Recipient Neurocle Releases Deep Learning Vision Software Neuro-T & Neuro-R Version 2.0


Deep learning startup Neurocle announced that it officially released Version 2.0 of no-code deep learning vision software, Neuro-T and Neuro-R. Neuro-T and Neuro-R allow users to solve image analysis problems ranging from manufacturing to healthcare by easily make customized deep learning model in industries.





Δ Deep learning software Neuro-T and Neuro-R


Some key updates to the software include the addition of the feature, Anomaly Detection. Anomaly Detection is a technique used to separate abnormal data from normal data. A model using Anomaly Detection can achieve this after training with only a single type of images (normal data). When it detects images that deviate from the pattern observed during training, it will mark them as anomalies. Anomaly Detection is perfect for cases where there are a limited number of anomaly images.


Additionally, starting from version 2.0, users can adjust the Threshold value, which allows users to have greater control over model behavior.

Coinciding with the 2.0 release of Neuro-T and Neuro-R, Neurocle was selected as a recipient of the Ministry of Science and ICT’s “AI Voucher” support funds, a government initiative to encourage adoption of AI technology developed by startups and small and medium-sized enterprises. A spokesperson from Neurocle said of the news, “We are excited to be a recipient of AI Vouchers. It will help us provide our businesses customers with the newest AI business solutions.”

Δ AI Voucher System (Source: Ministry of Science and ICT)


Meanwhile, on July 27, Neurocle will showcase the latest versions of its deep learning vision software (Neuro-T and Neuro-R) during KOREA MAT, one of Korea’s largest distributions industry conventions. Neurocle will demonstrate how businesses in the distributions industry can radically improve workflow by adopting new functions of version 2.0 as well as Detection (detects object quantity and location) and OCR (text recognition).


Source: https://www.aitimes.kr/news/articleView.html?idxno=17114