~68% of factory defects can be attributed to human factors in the quality control process.
✅Automate your processes with @akridata :
akridata.ai/guides/the-tru…
Protect your civilization. Arrest and deport those Islamists. The Muslim Brotherhood has turned your universities into war zones against Jews. Harvard is now a Hamas-Hezbollah recruiting ground. Ban them, like the UAE did. You can't be more Muslim than us.
@visegrad24
An intro into what Vision and AI brings, major problems and latest advancements - thanks to Simon Kriss for having me!
@akridata has your back starting with a vision-based system or save time & reduce cost on improving your existing one.
linkedin.com/feed/update/ur…
This blog explores how pooling enhances feature extraction in deep learning models, with an emphasis on pooling in CNNs, and breaks down the different types of pooling, their benefits, and practical applications.
akridata.ai/blog/pooling-f…#pooling#deeplearning#CV#AI#ML
Incorporating best practices in visual data analysis can improve the interpretability and performance of AI models, making it a foundational element for organizations working with computer vision applications.
akridata.ai/blog/best-prac…#visualdata#bestpractices#datascience
Check out our recent blog where we’ll break down the differences between data curation and data labeling, explore why each is important, and show how they work together to improve AI model performance.
akridata.ai/blog/data-cura…#datacuration#datalabeling#AI
Akridata’s Inspection Studio determines whether identified irregularities in medical devices are acceptable cosmetic variations or unacceptable functional defects that could negatively impact device performance.
akridata.ai/medical/#medicaldevice#deviceinspection
Managing extensive video datasets can be particularly intricate. Multiple scenes, diverse content, and the need for precise segment extraction can complicate the curation process.
Data Explorer introduces a nuanced approach to video curation.
akridata.ai/blog/split-vid…
Akridata’s Data Explorer uses advanced clustering and filtering techniques to automatically identify and label rare scenarios in AI datasets, saving time and enhancing model training for better accuracy.
akridata.ai/finding-edge-c…#edgecasedetection#labeling#AImodels
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