May 25, 2022
【Press release】LeapMind announces “Efficiera® Anomaly Detection model”
Focusing to visual inspection, edge AI enables fast and secured manufacturing DX ‐Training with only a few normal data, all AI operations completes on edge devices‐
May 25, 2022– Tokyo Japan, LeapMind Co., Ltd., today announced a new Deep Learning model “Efficiera Anomaly Detection model” based on its ultra-low power consumption AI inference accelerator IP "Efficiera®" and will be available from June, 2022. This specializes in visual inspection for the manufacturing industry and contributes to reducing security risk and labor shortage at the manufacturing site.
Features of “Efficiera Anomaly Detection model”
•Training completes with only normal data
Annotation work is not required which is often outsourced, no necessity of concluding non-disclosure agreement. Avoids the need of large amount of defective data, and training completes just in a few seconds which enabling rapid introduction of AI to the manufacturing site
•Completes both inference and training on small edge device with FPGA
No need of send image data outside the company, the risk of information leakage is reduced, and complicated non-disclosure agreements are not required which could lead to labor savings Can be used in environment without network
•Re-training can be done without an AI engineer
Visualization of abnormal areas by heat map.
AI training results can be saved and reloaded (redo and version management) easily on site which makes it easy to use to those companies that have difficulty in securing IT human resources.
The needs of automation in the manufacturing industry has been growing due to the chronic understaffing problem. AI usage is brought to the attention for visual inspection for quality check, but the challenges are the shortage of IT human resources and high cost of equipment. Other challenges are collecting defective datas for AI training and the complication of high-mix low-volume production due to the diversification demand and this may be cases where the support of AI engineers is required for AI retraining due to a change in the inspection target. Efforts to deal with these issues are also becoming a hurdle to adoption.
LeapMind has been developing an AI inference accelerator IP “Efficiera®” which can embed deep learning technology into various edge devices to popularize the devices with deep learning technology to the world to make people’s lives convenient. A newly developed “Effciera Anomaly Detection model” lowers the hurdle to introduce AI to visual inspection by using its own unique “Extremely low bit quantization” technology. The key feature of this deep learning model is that both inference and training can be completed on small edge devices with FPGA. Comparing the case using cloud AI, it has an advantage that there is no need to send inspection target images from the device itself which reduces the risk of data breach, contributes to reduce broadband infrastructure and cloud service usage fee. Also, compared to the case of using on-premises GPU server, it resolves concerns of the equipment cost and the installation space. The training can be completed in a few seconds only with a few dozens of normal product images and no necessity of collecting defective datas. This requires no annotation work and makes it possible to detect unexpected abnormalities and lowers the risk of only detecting trained defect targets. This model visualizes the part judged by AI as abnormal with a heating map and retraining operation is very simple so that it makes on-site adjustment easy without the support of AI engineers even on high-mix low-volume production lines. Since the training result is saved in a few MB of data and can be used for inference later, it is easy to redo the wrong training. This will help boost DX in the manufacturing industry even for companies that have difficulty in securing IT human resources or companies that have manufacturing bases in rural areas where broadband networks cannot be used.
Image : visual inspection using the "Efficiera" anomaly detection model. Abnormal parts of defective products can be seen at a glance by visualization with a heat map
Based on our vision “To provide key technologies to bring next-generation information devices into reality”, we will continue to strive to the realization of more convenient lives for people by realizing edge AI into practical use.
Efficiera is an ultra-low power AI inference accelerator IP specialized for CNN inference processing that runs as a circuit on FPGA or ASIC devices. The "extremely low bit quantization" technology minimizes the number of quantization bits to 1 - 2 bits, maximizing the power and area efficiency of convolution, which accounts for most of the inference processing, without the need for advanced semiconductor manufacturing processes or special cell libraries. By using this product, deep learning functions can be incorporated into a variety of edge devices, including consumer electronics such as home appliances, industrial equipment such as construction machinery, surveillance cameras, broadcasting equipment, as well as small machines and robots that are constrained by power, cost, and heat dissipation, which has been technically difficult in the past. LeapMind provides three Deep Learning models - Efficiera Object Detection model, Efficiera Noise Reduction model and Efficiera Anomaly Detection model. Visit product website at https://leapmind.io/products/efficiera-ip/
LeapMind Inc. was founded in 2012 with the corporate mission "To create innovative devices with machine learning and make them available everywhere." Total investment in LeapMind to date has reached 4.99 billion yen (as of May 2021). The company's strength is in extremely low bit quantization for compact deep learning solutions. It has a proven track record of achievement with over 150 companies, many of which are centered in manufacturing, including the automobile industry. It is also developing its Efficiera semiconductor IP, based on its experience in the development of both software and hardware
Head office: Shibuya Dogenzaka Sky Building 3F, 28-1 Maruyama-cho, Shibuya-ku, Tokyo 150-0044 Representative: Soichi Matsuda, CEO Established: December 2012 URL: https://leapmind.io/en/
*LeapMind, Efficiera and logo are trademarks or registered trademarks of LeapMind Inc. *The information in the press release is current as of the date of announcement.
Media Contact Efficiera Division, Marketing and Communication Team, LeapMind Inc. Phone: 813-6696-6267 Email: firstname.lastname@example.org