Cascade Classification – Boosting Run-Time Performance of Classification-Tasks

Posted Leave a commentPosted in Computer Vision, Machine Learning, Tutorial

In many applications, real-time image analysis is mandatory. An industry-robot, which needs five seconds to recognize objects on an image is mostly very limited in usage. On the other hand latest applications require detecting objects and positons as accurate as possible. Using some high-performance GPUs optimized for deep learning and latest research advances like YOLO, […]

Data Augmentation – What is it?

Posted Leave a commentPosted in Computer Vision, Deep Learning, Machine Learning, Tutorial

Especially in the field of Machine Learning, you will read about an approach called “Data Augmentation”. This idea is great to boost the performance of your Machine Learning Models. First at all, we want to clarify what Data Augmentation means. Data Augmentation is an approach to generate more training samples for your model without actually […]

“Do It Yourself” – Optical Character Recognition

Posted Leave a commentPosted in Computer Vision, Machine Learning, Tutorial

Today we have a look at how you can create a text recognition software with simple methods without being dependent on Tesseract and similar. We will get to know the following: Semantic Local Binary Patterns (S-LBP): As feature extraction method1 Histograms: As method to efficiently merge/collect features k-Nearest-Neighbor Classifier: As simple method to classify samples […]

Developing a Self-driving Car – Day #9 & #10

Posted Leave a commentPosted in Computer Vision, Deep Learning, Machine Learning, Project

YAY! I kind of did it! I created a reasonably fast traffic sign/light detector. The software truely does not work perfectly and also detection of gray/white signs is still quite hard. However it basically works, especially for red, blue and yellow traffic signs using only really limited hardware. There is still much room left to […]

Developing a Self-driving Car – Day #5 & #6

Posted Leave a commentPosted in Computer Vision, Data-Mining, Deep Learning, Machine Learning, Project

So I finally found an architecture which seem to work pretty good. We also continued annotating images taken and labeled about 1000 more traffic signs/traffic lights. In total we now got about 3000 traffic signs/lights in our own database + 800 from the The German Traffic Sign Detection Benchmark. We applied a lot of data […]

Developing a Self-driving Car – Day #3

Posted Leave a commentPosted in Computer Vision, Data-Mining, Deep Learning, Machine Learning, Project

Today I was able to test my new CNN architecture and the extended dataset. However preprocessing and augmenting the annotated images took much longer than I expected it would (It took around of 1h manual postprocessing and ~3h automatic post-/preprocessing). I started training my new NN architecture. My goal was 120.000 iterations. This takes about […]

Developing a Self-driving Car – Day #2

Posted Leave a commentPosted in Computer Vision, Data-Mining, Deep Learning, Machine Learning, Project

Today I was able to build a very basic traffic sign recognizer based on Neural Nets (using Selective Search and Deep Convolutional Neural Nets, so a basic RCNN2 approach). I used the annotated files of “The German Traffic Sign Detection Benchmark”1 to train my net. I implemented the net using the Deeplearning Framework Caffe. However […]