Digital computers have served us well for decades, but the rise of artificial intelligence demands a new kind of computer: analog.
About Us:
Advance Ultravision is the main distributor of Industrial Machine Vision products and components in Malaysia. We specialized in Machine Vision software such as Machine Learning, Deep Learning, Machine Vision Software Library, and 3D Machine Vision.
Vincent Hua is a Malaysia-based Machine Vision sales engineer, an ex-Machine Vision cum Automated Machine software engineer. Specialized in a machine vision system for Semiconductor / Electronics / Automotive sector.
The automation of processes in greenhouses using machine vision technologies makes it possible to meet the increasing demand for quality, hygiene, and food safety.
With the help of machine vision, harvesting robots able to detect, classify and cut ripe crops. Also, multispectral imaging and deep learning technologies enable early detection of nutrient deficiency or signs of disease to ensure the best quality yields.
Learn more about machine vision for agriculture solutions:
Advance Ultravision is the main distributor of Industrial Machine Vision products and components in Malaysia. We specialized in Machine Vision software such as Machine Learning, Deep Learning, Machine Vision Software Library, and 3D Machine Vision.
MVTec Software GmbH is a leading international manufacturer of software for machine vision used in all demanding areas of imaging like the semiconductor industry, surface inspection, automatic optical inspection systems, quality control, metrology, medicine, or surveillance. In particular, software by MVTec enables new automation solutions for the Industrial Internet of Things by providing modern technologies like 3D vision, deep learning, and embedded vision.
Vincent Hua is a Malaysia-based Machine Vision sales engineer, an ex-Machine Vision cum Automated Machine software engineer. Specialized in a machine vision system for Semiconductor / Electronics / Automotive sector.
With the MVTec Deep Learning Tool, it’s possible to train a deep-learning-based classification model from scratch.
First, we import images of your application – using the folder structure, the Deep Learning Tool can assign labels automatically. We can then review our data by filtering the images according to these labels.
After that, we train the model using transfer learning and pre-trained networks provided by MVTec.
Lastly, we can review the trained model in detail, using a confusion matrix, heatmaps, and more. Deep Learning Tool(version 0.5) used in this video.
Advance Ultravision is the main distributor of Industrial Machine Vision products and components in Malaysia. We specialized in Machine Vision software such as Machine Learning, Deep Learning, Machine Vision Software Library, and 3D Machine Vision.
MVTec Software GmbH is a leading international manufacturer of software for machine vision used in all demanding areas of imaging like the semiconductor industry, surface inspection, automatic optical inspection systems, quality control, metrology, medicine, or surveillance. In particular, software by MVTec enables new automation solutions for the Industrial Internet of Things by providing modern technologies like 3D vision, deep learning, and embedded vision.
Vincent Hua is a Malaysia-based Machine Vision sales engineer, an ex-Machine Vision cum Automated Machine software engineer. Specialized in a machine vision system for Semiconductor / Electronics / Automotive sector.
Plant protection is an important component of crop cultivation to ensure high yields and best quality. Growing objections and increasingly strict regulations of traditional protection methods are challenges that have to be faced – today and in the future.
Therefore, it is necessary for crop protection products to be put to particularly efficient use. With the help of industrial image processing, it is possible to distinguish between crops and weeds in real time during the spraying process and to precisely apply the agent.
With Deep OCR, MVTec introduces a holistic deep-learning-based approach for optical character recognition (OCR).
Deep OCR can localize numbers and letters much more robustly, regardless of their orientation, font type, and polarity. The ability to group characters automatically allows the identification of whole words. This improves the recognition performance significantly and avoids the misinterpretation of characters with similar appearances.