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Features:

  • MGTL03V and MGTL03VC are suitable for 12 Mega Pixel
  • MGTL0345V is suitable for 25 Mega Pixel
  • Long working distance, 150mm – 160mm with excellent brightness
  • Variable iris, possible to adjust DOF
  • Suitable for measurement and inspection, required for high accuracy

Features:

  • Compact design, suitable for small device
  • Adjustable iris, possible to adjust depth of field
  • TV distortion less than 0.05%
  • MGTL05-1.1 is suitable for 1.1”
  • MGTL0275V-2 is suitable for 2/3”(φ12.8mm)

 

Features:

  • 4 Mega Pixel – 9 Mega Pixel telecentric lens series for 1”
  • 0.275x and 0.37x are available
  • MGTL0275V is designed for long working distance, 150mm
  • Excellent relative illumination
  • Adjustable iris, possible to adjust depth of field

Features:

  • Suitable for 3.45μm
  • Line up : 0.14x, 0.17x, 0.19x and 0.22x
  • Long working distance, WD150mm
  • WD180mm type is available for 0.14x
  • Compact design with low magnification
  • Adjustable iris, possible to adjust depth of field

 

Features:

  • Suitable for 3.45μm
  • Excellent brightness, compared to Mega Pixel telecentric lenses
  • Adjustable iris, possible to adjust depth of field
  • Compact design
  • Reduce hot spots of co-axial illumination
  • MGTL10V and MGTL10VC are suitable for 1.1”

 

Features:

  • Compact and suitable for customized optical systems
  • φ16mm telecentric lens
  • R type is improved contrast and relative illumination

 

Features:

  • High resolution and compact design
  • Suitable for various applications, alignment, inspection, measurement, etc..
  • Adjustable iris for 0.5x and 0.7x
  • Compatible with 3 Mega Pixel of 1/1.8”

 

Features:

  • Suitable for vacuum chamber, working environment in high temperature, etc.., required for long WD
  • 4x and 6x are available
  • All models are designed for co-axial illumination

 

Features:

  • Suitable for applications required for long WD
  • Long WD, over 300mm
  • TL10C-310 is compatible with 2/3”
  • TV distortion is less than 0.00%

 

Features:

  • Short OI and High NA
  • φ16mm telecentric lens
  • R type is improved contrast and relative illumination

 

 

Features:

  • Suitable for best quality in 25 Mega Pixel ( 2.5μm/Pixel )
  • Super high resolution
  • Adjustable the depth of field and the Contrast
  • Magnification can be converted from 0.35x to 0.7x by using front converter

Features:

  • Telecentric lens at the whole range of magnification
  • Suitable for 5 Mega Pixel
  • Magnification of VTL0513 can be converted from 0.25x – 2.6x by using front converter
  • Reduce relative illumination
  • TV distortion less than 0.01%
  • VTL0513 is suitable for large format, up to 1.1” even though original optical design is for 2/3”

Independent learning encompassing the entire process of real-world work

Students can experience the entire process of data input, labeling, model training and reporting. By practicing the entire process of deep learning model training, students can quickly grasp the concepts of deep learning.

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Real-time results within a standard class period with fast model training

Through fast model training, you can check the model training results within a regular class period. 

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Practical learning with a variety of fun projects

Bring your ideas to life by running your models on a Jetson or a PC. Encourage students by displaying their work in action.

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Unlimited possibilities with multiple environments and devices

From low-spec embedded boards to CPUs and GPUs , you can apply and utilize the model on any device. Integrate your model to the desired system using the programming language of your choice.

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Reduced tack time with fast detection through optimization

During equipment setup, calculation methods are optimized to fit each equipment. Apply this technology to major manufacturing fields where tack time is crucial.

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Diverse options in model application through APIs

Accomplish more than just a simple delivery of model inference results—utilize various APIs to generate results from multiple models in creative ways.

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Auto-optimization customized
to project data

Since Neuro-T can create a model with the best performance through automatic optimization of deep learning model structure and training parameters, project managers can leave the difficult work to Neuro-T and focus on what they do best.

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Convenient maintenance with Fast-Retraining

If models require retraining due to addition or changes in training data, our Fast Retraining function can reduce the training time without compromising the performance of the existing model, enabling quick and easy maintenance.

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Low entry barrier with intuitive UX/UI

The intuitive UX/UI makes it easy for anyone to use our software. The operator can quickly learn how to use the software to apply deep learning to their project, and the manager can easily manage the project.

 

Various hyperparameter tuning

You can freely optimize models however you want by adjusting various parameters regarding the data and the overall model. Through easy GUI-based parameter searching, apply deep learning to any field of research. 

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Higher utilization of deep learning, regardless of expertise

Hardware/software configuration and coding skills are no longer necessary for deep learning. Align your team to the highest skill level with the intuitive GUI that allows researchers to focus on model training.

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The work of 3 experts in 1 software

It usually takes a team of three: a data manager, a labeler, and a model engineer. Minimize your team by managing all your tasks. One operator can fulfill the role of a three person team with Neuro-X.

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