We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Weka Model for automated microplastics segmentation in ImageJ
Summary
This is a machine-learning model file (Weka segmentation for ImageJ) used to automate the identification of microplastic particles in microscope images — a software tool rather than a primary research article.
This is the model file for the trainable Weka segmentation in ImageJ, which can be applied to 2D RGB images.
Sign in to start a discussion.
More Papers Like This
Weka Model for automated microplastics segmentation in ImageJ
This is a duplicate of the Weka ImageJ segmentation model file (same as ID 2815) — a software tool rather than a primary research article.
Computer vision segmentation model—deep learning for categorizing microplastic debris
Researchers developed a deep learning computer vision model for automatically categorizing beached microplastic debris from images. The segmentation model was trained to identify and classify different types of microplastic particles, reducing the need for time-consuming manual counting and laboratory analysis. The study suggests that automated image-based detection could enable more scalable and consistent monitoring of microplastic pollution along coastlines.
Microplastic Binary Segmentation with Resolution Fusion and Large Convolution Kernels
Researchers developed an improved machine-learning model to automatically detect and segment microplastic particles in images, achieving better accuracy than previous approaches by combining multi-resolution image analysis with large convolution kernels. Reliable automated detection tools are essential for scaling up microplastic monitoring, since manual identification is too slow and inconsistent for the volumes of environmental samples that need to be processed.
Proceeding the categorization of microplastics through deep learning-based image segmentation
Researchers developed a deep learning-based image segmentation method using Mask R-CNN to automatically identify and classify microplastic shapes in microscopic images, demonstrating a practical step toward standardized and automated microplastic categorization.
Automatic Counting and Classification of Microplastic Particles
Researchers developed an automatic system for counting and classifying microplastic particles in marine samples, applying image analysis techniques to address the growing problem of plastic debris entering the food chain via marine species ingestion.