Innovation Lab

We Develop Vision for Machines and Robots with Deep Learning and AI

In our senswork Innovation Lab in Munich, we are continuously working on new solutions for optomechanical inspection tasks using deep learning and AI. We take up new knowledge and technologies for industrial image processing at an early stage in order to make them usable in industry and research -paving the way for the future of quality assurance in the machine vision industry.

 

 

Neuralyze by senswork

senswork has developed the deep learning software Neuralyze for quality tests with complex test objects. The efficient inspection software is suitable for tasks that cannot be solved with conventional image processing. This includes, for example, inspections of test objects with transparent, reflective, curved or inhomogeneous surfaces or the detection of products with a high variance of features.

A self-learning method with neural networks is implemented to assess characteristics. A large amount of image data is required for the training process, with the help of which the algorithm is then optimized.

With Neuralyze, for example, cracks, scratches, voids, fibers, grooves, hair, oxidation, delamination or inclusions can be detected.

 

Your Contact Person

Markus Schatzl senswork
Markus Schatzl

+49 (0)89 215 298 46 0
markus.schatzl@senswork.com

senswork GmbH
Innovation Lab
Friedenstraße 18
81671 München

 

 

Projects

Surface Inspection of Cylindrical Aluminum Bodies
Examination of Surface Damage Through 360° Endoscopic Inspection
Praline Box Inspection
Location & Position Recognition and Completeness Confirmation using Deep Learning
Quality Assurance for First Aid Kits
Location Detection and Completeness Confirmation using Deep Learning
Reading a Raised Inscription on Smartphone Cases
Robust Reading of the Label using Deep Learning based OCR
Reading the „best before“ date on beverage bottles
Font Reading for Transparent Packaging using Deep Learning
Reading the „best before“ date on bottoms of bottles
Font Reading for Transparent Packaging using Deep Learning
Error Detection for Tortillas
Optical Inspection using Deep Learning
Quality assurance for LED curcuit boards
Error detection with the help of Deep Learning
Inspection of Glass Vials
Defect Detection on Reflective Surfaces using Deep Learning
PCB assembly verification of smartphone boards
Component Placement Inspection using Deep Learning
Spark Plug Inspection
Location Detection and Completeness Confirmation using Deep Learning
Air Filter Fault Detection
Examination of Surface Damage using Deep Learning
Recognition of Fonts for Ring Clamps
Optical Inspection of Surfaces with Inhomogeneous Topology

FAQs – Frequently Asked Questions

In our Innovation Lab we focus on deep learning and image processing in order to be able to better solve the complex tasks of our customers.

1. What is deep learning or AI and what does senswork offer?

Deep learning and Machine Learning (DL / ML) are methods used in the research field of ​​artificial intelligence (AI). AI is originally a domain from computer science, the aim of which is to model software in such a way that it is capable of learning to a certain extent and, in terms of its interactions, indistinguishable from human actions.

The discipline has gone through several hype and consolidation phases over the past 65 years. In the course of the development of complex application frameworks and an enormous increase in the performance of computing hardware, a remarkable climax has been reached in recent years.

Although machine learning in image processing has been used in productive systems for more than 20 years, a number of new, methodical approaches open up possibilities here to significantly expand the scope of application and to use this technology on a broad basis.

For the use of DL / ML processes in image processing, senswork offers comprehensive support throughout the entire planning and integration process. When selecting a suitable toolkit, we are independent and orientate ourselves towards the optimal solution - this can consist of using our own deep learning software as well as the libraries of well-known manufacturers. Of course, we are also available to our customers with regard to advice, training and implementation as a single service.

2. What is our approach to developing Deep Learning and using it for Feasibility Studies?

A non-binding consultation is essential for inquiries about new image processing systems. From our experience, it is usually easy to assess whether the requirements can be solved with conventional methods, deep learning or machine learning, or possibly not at all.

With DL / ML systems, we always carry out a feasibility analysis in advance. For such studies, image data of the process to be checked are necessary, which either already exist at the customer's premises or which we record on site with an image processing system to be designed.

The basis of the implementation of DL / ML applications at senswork is that we carry out feasibility studies free of charge, but the customer undertakes to commission if the study proves successful implementation.

3. What problems can deep learning solve?

Deep learning (DL), machine learning (ML) and artificial intelligence include processes that implement self-learning methods for assessing characteristics with neural networks.

Often these are tasks that humans can solve intuitively. At the same time, however, they are difficult to describe and thus evade or have evaded the rule-based procedures that have prevailed to date.

With DL / ML there are now a number of powerful tools to deal with such applications efficiently. Many difficult questions in image processing that have not yet found a solution can now be solved very well. It is therefore advisable in any case to subject previously unsolvable inspection tasks to a feasibility analysis again.

4. For what kind of projects has senswork used deep learning and AI in image processing?

In 2D applications, deep learning / machine learning is particularly strong for tasks on diffuse, inhomogeneous surfaces, in which the error features have a wide range. This includes:

  • Die-casting technology: detection of cracks and cavities on rough surfaces
  • Surface inspection: grooves, grinding marks, inhomogeneities, planarity defects
  • Particle detection: detection and classification of contaminants
In the area of 3D applications, successful results can be achieved, especially with test objects with irregular shapes or naturally caused shape variations:
  • Seal seam inspection: quality and tightness of weld seams
  • Classification: assessment of plants and natural products
5. What makes senswork a thought leader in the field of deep learning and image processing?

senswork has many years of experience in the industrial image processing sector, due to several employees who deal with issues in this industry, which has existed for more than 30 years, both in management and developer positions. We know the entire breadth of image processing and thus also the depths, trends and hypes.

Classification methods that have a certain overlap with the service promises of DL / ML have been used in industrial image processing for 20 years, so that the processes are not always as new as they are presented in the media.

Standardized toolkits and the enormous increase in performance in the hardware area are indicative of the strong surge in recent years. In combination, this enables things with a scope of complexity, the practical realization of which was unthinkable ten years ago. We have been accompanying this development for many years.

 

 

Expert Interview

Find out more about deep learning in an interview with Markus Schatzl, head of the senswork Innovation Lab in Munich.

Click here for the complete interview

 

 

Membership in the field of AI

 

 

 

 

 

 

 

 

 

 

It will load necessary cookies, Google Fonts, Google Maps, OpenStreetMap, Youtube and Google Analytics. More details in our privacy policy and our imprint.