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Spring’16 perClass course

perClass Machine Learning course for R&D specialistsLast week, we had our Spring 2016 course. This time we had a very nice group of professionals working on defect detection, high-throughput agricultural quality control and traffic vision applications such as license plate recognition. As all the applications were based on imaging, we put more attention to extraction of image features (both at the local level of image neighborhoods and at the level of segmented-out objects). As usual in perClass courses, the participants took first steps on their own problems. We also discussed Deep Learning approach and delved into the basic building blocks of convolutional neural networks. (0) Comments


Traffic accident detections in tunnels

real-time acoustic accident detection with perClassIn a tunnel, a prompt detection of a traffic accident is crucial. It not only allows for an automatic help call, but it can also prevent more vehicles to enter and get involved. All this within seconds from the accident, way before any help could be on the location. Such alert system, based on acoustic signal processing, has being developed by Joanneum, the top Austrian research organization. perClass was selected as a platform to develop recognition algorithms and also as the real-time deployment solution processing the live data from microphone arrays.
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Recent research publications using perClass

recent research papers using perClass Toolbox delivering Machine learning in Matlab

Happy to share several publications summarizing recent research that used perClass software.

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Notes from the autumn perClass course

perClass machine learning course for data scientistsLast week, we gave our autumn perClass training course. We welcomed in Delft a group of seven participants from Austria, Germany, Denmark, Sweden and the Netherlands.
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perClass presentation at NHL symposium

perClass at NHL symposium on data science Come and join us at the NHL Symposium on computer vision, data science and parallel computing in Leuuwarden on 3rd December 2015!

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