in Computer Vision and Machine Learning
in Computer Vision and Machine Learning
Our mission is to deliver open source C++ libraries for numerical computation for the purposes of conducting computer vision and machine learning research. We teach computers to understand the visual world.
About Project X Research
We perform research on mathematically well-founded methods in computer vision and machine learning. The main focus is on techniques using partial differential equations and variational methods. We are interested in all aspects of these techniques, including mathematical modelling, well-posedness analysis, efficient algorithms for sequential and parallel computer architectures, and medical applications.
Human personality classification. How, in principle, can one measure a complex and, in fact, unique human personality with a finite number of labels? Ascribe a human to one of a few categories? If it seems impossible to solve such a task, the human brain copes with it with a hurrah. We, actually, from the first […]
After 3 years of work, 5 journeys to Tenerife island, 10.5 thousands of frames, 235 Gigabytes of data I am proud to present you this timelapse, which carries a part of astrophotography and the unique nature of the Teide National Park. There are only a few places in the world where you can go up […]
Natural Gas (Chart 1) has reached a 3-year high (Chart 2) in terms of short positions of commercials. This fact is based on recent Commitment of Traders Report (CoT) and indicates that it is more likely that the price will fall. The observation of the net positions of the commercials also support this conclusion. The net positions of the commercials have […]
Brent oil, gasoline and wheat (SR) have reached a 3-years high in terms of short positions of commercials. This is an extreme and it indicates that it is more likely that the price will fall. This interesting fact is supported by the net positions of the commercials, which have reached a bearish area compare to […]
DGM library v.1.6.0 has been just released We are glad to present our next big release of DGM, v.1.6.0, which summarizes the v.1.5.x line with further improvements and bug fixes. This is the first cross-platform release: since now on the DGM library is available also for macOS. The binaries built for macOS High Sierra (OS […]
Introduction The Vaihingen-DL dataset contains aerial images of Vaihingen village in Germany, associated with corresponding digital surface models (DSM) and two ground truth images – one for the base and the second – for the occlusion layer. Base layer Occlusion layer class 0 Road class 0 Void class 1 Traffic island (asphalt) class 1 Tree […]
Platinum has reached a 3-years low in terms of short positions of commercials. This is an extreme and it indicates that it is more likely that the price will rise. This interesting fact is supported by the net positions of the commercials, which have reached a bullish area compare to the last 52 weeks. Counting […]
Introduction The EMDS dataset contains environmental microorganism (EM) images downloaded from the Internet, associated with corresponding binary ground truth images. In total there are 21 classes of EMs. Each class is represented with 20 EM images with the corresponding binary ground truth bitmap. In ground truth images, EMs are marked with white (value: 255) and […]
Right after Christmas OpenCV 3.4 update and before the New Year we are glad to present the latest and the greatest DGM 1.5.3: The library for Conditional Random Fields with OpenCV. This release includes three new classifiers: OpenCV Artificial Neural Network OpenCV k-Nearest Neighbors OpenCV Support Vector Machine and from now on uses unit-testing based on […]
There is a wide variety of statistical models which may be applied to the semantic segmentation tasks. Let us now illustrate their impact on the computation of the label maps. For this purpose we use synthetic Green Field data-set, with 3 classes, described by two features. If we quantize all the features by 8 bit, […]