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V-ONE’s Solution

  • Medical & Pharmaceutical
    • Ultrasonic imaging diagnosis
    • Reagent classification
    • Culture cell inspection
    • Syringe inspection
    • Fluid foreign body inspection
    • Pill surface inspection
  • Display & Secondary Battery
    • Indentation foreign body inspection
    • Inspection of foreign substances, cracks and burrs
    • Scratch inspection
    • Cell phone surface inspection
    • Lead defect inspection
    • Stain inspection
  • Spare Parts & Material
    • Metal bobbin surface inspection
    • Liquid capsule contents inspection
    • Rubber material surface inspection
    • Wire classification/defect inspection
    • Lead application inspection
    • Wafer crack inspection
  • Logistics & Distribution
    • Box/Packaging classification
    • Assemble parts classification
    • Monitoring for loss of items
    • Agricultural goods automatic classification
    • Consumer orders inspection
    • Packaging/Container OCR reading

withAI

Quickly develop solutions by using various models based on the V-ONE Solution*, and work easily, clearly through a user-friendly interface.

  • PRE Block

    Pre-processing algorithm to improve detection power of inspection images

  • AI Block

    API for learning and inference (inspection)

  • APP Block

    API for AI project

V-ONE M/V solution has been recognized for its technological prowess and quality excellence in successfully carrying out various machine vision projects such as displays and secondary batteries.

Feature

  • V-ONE solution has a scalability and flexibility respond to various business needs.

  • Provides the ability to inspect various models in one task as needed.

  • Items that could not be inspected using existing inspection equipment can be detected.

  • Rapid inspection possible by supporting self-developed high-speed processing technology and multi-parallel processing technology.

  • Supports an optimization module for inspecting large amounts of image data.

  • Based on the block structure, users can only use the blocks they want.

  • Detection power is improved by suggesting specialized models depending on the inspection target.

  • Supports models that can be used in various fields such as manufacturing, medical care, materials, parts, distribution, and logistics.

Constitution

    • Customer
      request

    • Data collect & processing

  • PRE Block

    • Customer data processing
    • studying by Processed image
    • rule base pre processing algorithm for increase inspection power
  • AI Block

    • Object
      Detection

    • Segmentation

    • Classification

    • Anomaly

    • Easy and intuitive work with labeling tools provided
    • Detection class definition
    • Start learning immediately after checking labeling
    • Continuous model advancement
    • Multi-learning support (Multi GPU) model creation
    • Optimization model transformation
    • Model validation
    • Model quality check by appropriate inspector
    • APP Block

    • V-ONE
      Solution

    • Inspection model provided
    • API support for AI projects
    • Supports S/W customization in the way the customer needs
    • Support method (project, module, consulting)
    • Equipment development*
    • Optical module + model + API*
    • Model + API*
    • Support model & Consulting, Project

    • Customer

  • Equipment*

      • AOI
      • AMI
      • DMS
      • Etc.
    • withAI

  • Part’s (Module)*

      • Optic
      • V-one Solution
      • withAI
      • Display
      • Secondary battery
      • Medical
      • Material
  • Application*

    • withAI

    • API

Detail View

withAI

PRE Block

Preprocess

  • Auto-Labeling
  • Auto-Tuning
  • GAN (Generative Adversarial Networks)
  • Algorithm for improving video quality
  • Algorithm which is adjust shape for suitable image of model
  • Algorithm of simplifying model to improve model accuracy
  • Algorithm for classification
  • Algorithm of converting frequency for speckle inspection
  • Algorithm of feature extraction from image
  • Algorithm of finding shape in image information
  • Neural network (MLP)
  • Customizing Module

withAI

APP Block

Application

  • Provide public Lib for AI model inspection
  • ONNX model provided
  • Optimized engine providing for inspection time reducing
  • C/S App through learning and inspection server operation provided
  • Mobile model provided
  • Provides for apps tailored to customer needs
  • Industry-specific business models provided
  • Customizing Module

withAI

AI Block

Object Detection

  • After classifying the object and detecting its location If it is determined to be an object, it is displayed as a rectangle
  • Detect multiple objects in one image
  • Using pre- trained model, improve detection accuracy and time reduction
  • Select an appropriate model according to the process and task pre-learning and inspection
Medical / Pharmaceutical
  • Model dedicated to pill surface inspection provided
  • Model dedicated to the inspection of foreign substances in injected fluid. Provided
  • Model dedicated to specimen bin classification provided
Materials
  • Model dedicated to metallic appearance inspection provided
  • Model dedicated to surface inspection of rubber materials provided
  • Model dedicated to electronic component/board inspection provided
  • Model dedicated to wafer surface inspection provided
Logistics
  • Model dedicated to product classification provided
  • Model dedicated to classification of agricultural products provided
  • OCR reading model provided
Display
  • Model dedicated to edge crack inspection provided
  • model dedicated to lead burr inspection is provided
  • Model exclusively for mobile phone surface inspection is provided

Segmentation

  • Classify objects by dividing into pixels, display location
  • Detect multiple objects in one image
  • Using pre- trained model, improve detection accuracy and time reduction
  • Select an appropriate model according to the process and task pre-learning and inspection
Med / Pharmaceutical
  • Ultrasound imaging diagnostic model provided
  • Cultured cell inspection & classification models provided
Materials
  • Model dedicated to wafer surface inspection provided
Display
  • Speckle inspection model provided
  • inspection models for cracks, foreign substances, contamination provided

Classification

  • Determine object type and classified
  • Determine one object in one image
  • Using pre- trained model, improve detection accuracy and time reduction
  • Expected improvement in output when fused with Pre-Block
  • Select an appropriate model according to the process and task pre-learning and inspection
Med / Pharmaceutical
  • Drug classification model provided
Logistics
  • Pre-Block combination, OCR reading model provided

Anomaly

  • Judgment into normal and abnormal binary types
  • Judged as normal/bad in one video
  • Learning time is fast as it learns only from normal images
  • Collecting poor training data Improves training time and detection accuracy by using pre-trained models
Parts/Materials
  • Provides a model for inspecting the presence or absence of lead coating on the board
Logistics/Distribution
  • Box damage inspection model provided

Applying Field

  • Medical & Pharmaceutical

    • Ultrasonic imaging diagnosis

    • Culture cell test - Live, Dead, Debris classification

    • Medicinal type/grade classification

    • Foreign substances in injected fluid, print inspection.

    • Classification by specimen container type

    • Pill breaks, scratches, color, and shape inspection

  • Material & Parts

    • Inspection of metal bobbins for nicks and scratches

    • Inspection of inner cable color for wire cross sections

    • Inspection of capsule contents for bubbles and bursting

    • Inspection of wafer scratch and speckle

    • Inspection of lead soldering application (none lead, over lead, less lead, short)

    • Inspection of rubber ring colored foreign matter, tear, and edge

  • Display & Secondary battery (Rechargeable)

    • Inspection for Edge crack & damage

    • Lead burr, open, short defect inspection

    • Speckle (dot, line, north pole) inspection

    • Mobile phone scratches, camera and fingerprint sensor scratches, and surface inspection for cracks

  • Logistics & Distribution

    • Sorting boxes on the move

    • sorting screws which for assembly of finished products

    • Automatic classification of agricultural products by size

    • Inspection of customer order item & ship and return product

    • OCR reading of packaging, containers, etc.

  • Foods & Packaging

    • Inspection of cosmetic containers for breaks, scratches, and foreign substances

    • Inspection of expiration date printing on packaging

    • Inspection of Can, bottle, canned food printing and damage

    • Inspection of contamination and foreign substances in food

  • Robotics Autonomous Driving

    • AMR (Autonomous Mobile Robots)

    • Location measurement and real time map generation

    • Path creation, avoiding object, collision prevention through Object detection technology

    • Prediction of drivable area using Segmentation

    • Reinforcement Deep learning-based multi robot and avoid obstacle, abnormal detection

    • Real time collaborative detection with camera detection and DDS combined sensors

Product List

withAI

Lite

withAI

Professional

withAI

Medical

Object-Detection
Instance Segmentation
Classification
Anomaly
Semantics Segmentation
Learning Model Small Large Large
Multi GPU 1 2 2
ONNX
Optimized Inference
Multi Threading
Auto Learning
Customizing

Logistics / Distribution

Industrial

Medical / Pharmaceutical

Specification

withAI Lite

withAI Professional

division Minimum specifications Recommended specifications
Train PC CPU Intel i7 or more Intel i7 or more
RAM 16GB 32GB
CUDA Compute Capability 3.5 3.5
GPU Geforce RTX 4070 (12GB or more) Geforce RTX 4090 (24GB or more)
OS Windows 10 x64, Windows 11 x64
Inference PC CPU Intel i7 or more Intel i7 or more
RAM 16GB or more 32GB or more
GPU Geforce RTX 4070 (12GB or more) Geforce RTX 4080 (16GB or more)
OS Windows 10 x64, Windows 11 x64
Develop environment Visual Studio 2017 or more

withAI Medical

division Minimum specifications Recommended specifications
Train PC CPU Intel i7 or more
RAM 32GB
CUDA Compute Capability 3.5
GPU GeForce RTX 4090 (24GB or more)
OS Windows 10 x64, Windows 11 x64
Inference PC CPU Intel i7 or more Intel i7 or more
RAM 16GB or more 32GB or more
GPU Geforce RTX 4070 (12GB or more) Geforce RTX 4080 (16GB or more)
OS Windows 10 x64, Windows 11 x64
Develop environment Visual Studio 2017 or more
Created by WISHWEB
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