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Improving data annotation with Superpixels

Improving data annotation with Superpixels To understand the need for superpixels in segmentation we must first understand what is image segmentation. Image segmentation consists in detecting specific regions in an image. In concrete terms, this means detecting the shape of objects of different categories in images. Therefore, when segmenting an image, we give a class … Continue reading Improving data annotation with Superpixels

What Workflow to Follow to Manage Model Accuracy Performance?

What Workflow to Follow to Manage Model Accuracy Performance? Introduction Enhancing a model performance can be challenging at times. I’m sure many of you would agree that you’ve found yourself stuck in a similar situation. You try all the strategies and algorithms that you’ve learned, yet performance does not increase significantly. As a result, we … Continue reading What Workflow to Follow to Manage Model Accuracy Performance?

Better Training Data, Better AI

Better Training Data Better AI. Since the 80's the AI paradigm has been Better Models =  Better AI. Today the limitations of this paradigm are clear: significant efforts for marginal performance improvements, restricted access to overspecialized engineers, low explainability, low control, and prohibitive project costs. @Kili Technology, we are believers. 3 years ago, Edouard d’Archimbaud … Continue reading Better Training Data, Better AI

My State-Of-The-Art Machine Learning Model does not reach its accuracy promise: What can I do?

My State-Of-The-Art Machine Learning Model does not reach its accuracy promise: What can I do? Data Quality as a first response Introduction The ultimate goal of every data scientist or company that builds ML models is to create the better model with the highest predictive accuracy in production. Usually, we start with state-of-the-art algorithms being … Continue reading My State-Of-The-Art Machine Learning Model does not reach its accuracy promise: What can I do?

Data annotation: leveraging interactive segmentation to achieve state of the art quality and speed

Data annotation: leveraging interactive segmentation to achieve state of the art quality and speed Machine learning models have proven to be extremely powerful for automating tasks. Automatic image recognition for example has seen an incredible leap thanks to the development of convolutional neural networks. We see that our models today have not yet reached their … Continue reading Data annotation: leveraging interactive segmentation to achieve state of the art quality and speed