Neurocle Neuro-T Auto Deep Learning Model Trainer

Highlights

Neurocle Neuro-T is GUI-based no-code deep learning software designed to simplify development of industrial vision inspection models without requiring extensive AI expertise.

Neuro-T combines data management, labeling, model training, and model evaluation in one environment while Neurocle’s Auto Deep Learning Algorithm automatically selects suitable model architectures and training parameters.

Complete Model Development Workflow

STEP 1

Data Management

Organize and manage inspection image datasets.

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STEP 2

Labeling

Prepare training data with integrated labeling tools.

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STEP 3

Model Training

Train and optimize deep learning inspection models.

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STEP 4

Model Evaluation

Review model performance before deployment.

Auto Deep Learning

Neuro-T automatically selects model architectures and hyperparameters for the training task, reducing the amount of manual configuration required to build a deep learning inspection model.

Users can begin training through the graphical interface while Neuro-T handles much of the underlying model optimization process.

Neurocle Neuro-T Auto Deep Learning Algorithm workflow

Features

AI-Assisted Labeling

Automated labeling tools help reduce the manual workload involved in preparing training datasets.

Neurocle Neuro-T AI-assisted labeling tools

Multiple Deep Learning Models

Configure different deep learning model types for a wide range of industrial vision projects.

Neurocle Neuro-T deep learning model types

GAN-Based Defect Generator

Generate synthetic defect images for applications where real defect samples are difficult to collect.

Neurocle Neuro-T GAN-based defect generator

Unsupervised Learning

Train models using only normal images for deep learning inspection when defect data is limited.

Neurocle Neuro-T unsupervised learning trained with normal image data

Flowchart & Inference Center

Connect multiple models for complex projects and review model performance within Neuro-T before deployment.

Neurocle Neuro-T Flowchart and Inference Center workflow

Built for Industrial AI Inspection

No-Code Development

Graphical tools make deep learning model development accessible without manually designing neural networks.

Reduced Manual Work

AI-assisted labeling and automated model optimization simplify repetitive development tasks.

Pre-Deployment Evaluation

Review trained models and multi-model workflows before moving them into production.

Applications

Semiconductor

Battery

Automotive

Electronics

Metal

Food & Beverage

Pharmaceutical & Biotech

Medical Devices