Classification
Classifies images to multiple defect categories.
Model selection
11 Deep Learning Models
for tackling Various
On-Site Challenges
11 Deep Learning Models for tackling Various On-Site Challenges
Achieve accurate and consistent data labeling with AI-powered labeling features.
Challenges from complex projects
Manufacturing sites are facing increasingly complex projects requiring more than one model to solve.
Challenges from complex projects
Manufacturing sites are facing increasingly complex projects requiring more than one model to solve.
Challenges from complex projects
Manufacturing sites are facing increasingly complex projects requiring more than one model to solve.
Challenges from complex projects
Manufacturing sites are facing increasingly complex projects requiring more than one model to solve.
Solutions
Largest model selection in the industry
Solutions
Largest Model Selection in the Industry
Solutions
Largest model selection in the industry
Supervised Models
Oriented Object Detection
Detects the number and locations of objects with varying orientations.
TBD
Patch Classification
Classifies high-resolution images by dividing them into small patches.
Optical Character Recognition
Recognizes text (English, Numbers, Special Characters) within images.
Segmentation
Detects the precise shape and location of defects at the pixel level.
Object Detection
Detects the number of objects and their locations within images.
Classification
Classifies images to multiple defect categories.
Object Detection
Detects the number of objects and their locations within images.
Patch Classification
Classifies high-resolution images by dividing them into small patches.
Oriented Object Detection
Detects the number and locations of objects with varying orientations.
TBD
Segmentation
Detects the precise shape and location of defects at the pixel level.
Optical Character Recognition
Recognizes text (English, Numbers, Special Characters) within images.
Classification
Image classification model for multiple defect types.
Segmentation
Detects the precise shape and location of defects at the pixel level.
Oriented Object Detection
Detects the number and locations of objects with varying orientations.
TBD
Patch Classification
Classifies high-resolution images by dividing them into small patches.
Object Detection
Detects the number of objects and their locations within images.
Optical Character Recognition
Recognizes text (English, Numbers, Special Characters) within images.
Preprocessing Model
preprocessing model
Alignment
preprocessing model
Preprocessing Model
preprocessing model
preprocessing model
Alignment
Preprocessing Model
preprocessing model
Alignment
preprocessing model
GAN (Defect Generator)
Generates synthetic defect images resembling actual defects.
Image Enhancement
Converts low-quality images into high-quality images.
TBD
Rotation
Automatically rotates original images to the correct orientation.
GAN (Defect Generator)
Generates synthetic defect images resembling actual defects.
Image Enhancement
Converts low-quality images into high-quality images.
TBD
Rotation
Automatically rotates original images to the correct orientation.
GAN (Defect Generator)
Generates synthetic defect images resembling actual defects.
Rotation
Automatically rotates original images to the correct orientation.
Image Enhancement
Converts low-quality images into high-quality images.
TBD
Alignment
Rotation
A preprocessing model that rotates images to the correct orientation.
Unsupervised Learning Models
Anomaly Classification
Classifies normal/anomaly images in the form of a heatmap, trained solely with normal images.
Anomaly Segmentation
Detects precise anomalous regions at the pixel level, trained solely with normal images.
Anomaly Classification
Classifies normal/anomaly images in the form of a heatmap, trained solely with normal images.
Anomaly Segmentation
Detects precise anomalous regions at the pixel level, trained solely with normal images.
Anomaly Classification
Classifies normal/anomaly images in the form of a heatmap, trained solely with normal images.
Anomaly Segmentation
Detects precise anomalous regions at the pixel level, trained solely with normal images.
Key features
Exclusive models for industrial challenges
High-performance deep learning models addressing various issues during vision inspections.
Overcoming data scarcity
Overcoming data scarcity
Synthetic Defect Generator GAN Model
Generate synthetic defect images that closely resemble actual defect with the Generation Center.
Unsupervised Learning Models
Train models only with normal images for high-performance deep learning inspection even with limited defect data.
Unsupervised Learning Models
Train models with normal images only for high-performance deep learning inspection even with limited defect data.
Synthetic Defect Generator GAN Model
Generate synthetic defect images that closely resemble actual defect with the Generation Center.
Unsupervised Learning Models
Train models only with normal images for high-performance deep learning inspection even with limited defect data.
Detecting fine defects in high-resolution images
Patch-based Models
Classify normal and defective regions without defect information loss by splitting high-resolution images into multiple patches.
Recognizing objects with varying orientations
Oriented Object Detection Model
Recognizes the number of objects and identifies their locations, even with varying orientations.
Product Introduction
Looking for training software built for real-world challenges?
Product
Looking for training software built for real-world challenges?
Auto Deep Learning Model Trainer
GUI-based training software for generating high-performance inspection models without deep learning expertise
Auto Deep Learning Model Trainer
Auto Deep Learning Training Engine
High-performance Auto Deep Learning training module for flexible integration on various systems.
Auto Deep Learning Training Engine
Insights from Neurocle
Find out more about our latest news, technical insights and industry trends.
Insights from Neurocle
Find out more about our latest news, technical insights and industry trends.
Insights from Neurocle
Find out more about our latest news, technical insights and industry trends.
Neuro-Tech
[Deep Learning 101] Understanding Deep Learning Through Images (Part 4): Labeling and Data for Model Performance
Neuro-Trend
April Trends – Is Korea’s Manufacturing Revenue Expected to Decline in Q2? (AI Talent / HBM / Semiconductor / Manufacturing)
Neurocle News
[Newsletter Vol. 5] Captivating the World! Neurocle’s AI Vision Recognized on the Global Stage
Learn more about Neurocle's
Auto Deep Learning technology
Learn more about Neurocle's
Auto Deep Learning technology