Deep Learning Software

EasyLocate

Deep Learning localization and classification library
Feb. 18, 2022
2 min read

AT A GLANCE

  • Localization and identification of objects/products/defects
  • Counting of objects
  • Supports data augmentation and masks
  • Compatible with CPU and GPU processing
  • Includes the free Deep Learning Studio application for dataset creation, training and evaluation
  • Only available as part of the Deep Learning Bundle

EASYLOCATE DATASHEET

EasyLocate is the localization and identification library of Deep Learning Bundle. It is used to locate and identify objects, products, or defects in the image. It has the capability of distinguishing overlapping objects and, as such, EasyLocate is suitable for counting the number of object instances. In practice, EasyLocate predicts the bounding box surrounding each object, or defect, it has found in the image and assigns a class label to each bounding box. It must be trained with images where the objects or defects that must be found have been annotated with a bounding box and a class label.

What Is Deep Learning ?

Neural Networks are computing systems inspired by the biological neural networks that constitute the human brain. Convolutional Neural Networks (CNN) are a class of deep, feed-forward artificial neural networks, most commonly applied to analyzing images. Deep Learning uses large CNNs to solve complex problems difficult or impossible to solve with so-called conventional computer vision algorithms. Deep Learning algorithms may be easier to use as they typically learn by example. They do not require the user to figure out how to classify or inspect parts. Instead, in an initial training phase, they learn just by being shown many images of the parts to be inspected. After successful training, they can be used to classify parts, or detect and segment defects.

Learn More

Request Information

By clicking above, I agree to Endeavor Business Media's Terms of Service and consent to receive promotional communications from Endeavor, its affiliates, and partners per its Privacy Notice. I also understand my personal information will be shared with the sponsor of this content, who may contact me about their offerings per their privacy policy. I can unsubscribe anytime.