Some libraries may be more suitable for basic image manipulation ... Some common techniques for image data analysis using Python include image segmentation, object detection, feature extraction ...

Source code for the paper: "Gaussian Random Fields as an Abstract Representation of Patient Metadata for Multimodal Medical Image Segmentation" ...

Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image ...

For professionals like the Lead AI Engineer or Senior AI Engineer, the Mistral Agents API represents a powerful addition to their AI toolkit.

'ZDNET Recommends': What exactly does it mean? ZDNET's recommendations are based on many hours of testing, research, and comparison shopping. We gather data from the best available sources ...

I already covered the changes that the team had made at the front of the MCL39 a while back but we didn’t have suitable images of the rear brake assembly to cover that effectively at the time.

Abstract: Anatomical image segmentation is one of the foundations for medical planning. Recently, convolutional neural networks (CNN) have achieved much success in segmenting volumetric (3D) images ...

Abstract: Automatic segmentation of medical images is a crucial step for lesion measurement in computer-aided diagnosis. Convolutional neural networks (CNNs) and vision transformers (ViTs) are widely ...

Kaizen rethinks cell segmentation by mimicking brain predictions. Using an iterative machine-learning approach to refine boundaries in crowded microscopy images, it enhances accuracy in tissue studies ...