Projects
To enhance Ducks Unlimited Canada (DUC)‘s capability for UAV-based surveillance of European Water Chestnut (EWC) through machine learning, we at Saiwa have previously implemented the initial version of the EWC detector software. In the second stage, we are in the process of finalizing the product’s features and upgrading its interfaces.The two primary features to be incorporated in this stage are as follows:
- Incremental learning for gradually training the deep network over time. This feature enables us to rectify false positive and false negative detections over time.
- Reporting the 3D universal coordinates of EWC locations using drone configuration and temporal GPS data.
We at Saiwa Inc. are pleased to announce that we have successfully completed an aluminium surface defect detection project in collaboration with AI-innovate Company for CastTechnology in Canada.
In this project, using machine learning techniques and the networks we provide in our Anomaly Detection service, we detect and localize the location of micro and macro defects on a casting line, including: crack, frost, frost patch, longitude frost and mold oscillation. This service is delivered via a simple user interface where users can run the defect detection APIs.
For more information about the project or if you find it interesting, please contact us at: support@saiwa.ai
Read Also: Surface Defect Detection
This is a corrective exercise mobile application which is developed for Android platform. Corrective Exercise is a technique that leverages an understanding of anatomy, kinesiology, and biomechanics to address and fix movement compensations and imbalances to improve the overall quality of movement during workouts and in everyday life. This technique is used to help assess and determine the root cause of imbalances and faulty movement patterns that lead to issues with posture, balance, and total body coordination.
For a long time, product quality control relies on manual examination in the manufacturing field. In the past several decades, automated surface inspection (ASI) have become more widespread as hardware and software technologies have developed rapidly. To lower labor costs and enhance examination efficiency, more factories start to employ embedded machines for product inspection. ASI platforms use special light sources and industrial cameras to capture the images of the product surface, and machine/computer vision technologies to filter out defective products, which can reduce labor greatly. High-performance cross-product ASI algorithms are urgently needed in manufacturing.
European water chestnut (Trapa natans) is an invasive floating-leaved aquatic plant that is capable of out-competing native species and altering Ontario’s aquatic ecosystems. In addition to ongoing control of known populations in Ontario, this species is designated as a “Prohibited Species” in Ontario under the Invasive Species Act, 2015 to aid in prevention, detection and control of the species. Ducks Unlimited Canada (DUC) performs surveillance and control of this species in eastern Ontario in attempts to eradicate existing populations and prevent the establishment of new ones.
RFDs are DNA sequences that induce a cleavage (cutting) reaction in a substrate strand in response to the presence of a target. In this project, we at saiwa team segmented and measured regions of interest (the dots that constitute the microarray) relative to the background in printed RFD images. Printed microarrays can be used to test for the presence of specific targets (i.e., bacteria). We used around 100 RFD images that were provided by Didar Lab., McMaster uni.
For more information please contact us via: info@saiwa.ai