Friday, May 17, 2019 (put topic here)¶
Participants: Thomas, Richard, Subir, Michael, Katharina, Josefine, Sophia, Maren, Malin, Ulf and Axel
Topics of today:
summary from last week
Preparations for meeting with man from Hermerle next Friday (24.5.)¶
(he is open for cooperation, we will see if we can make use of it)
presentation for him¶
(Thomas has further notes to this)
presentation (~10min):
intro what our backgrounds are/ cognitive science
intro to study project : what we are interested in - methodology —> came to idea to apply it to machine of sophia’s brother
classes what we want to sort –> include picture of decision tree which Josefine draw
explain our toolbox - state openness to other methods
share extraction of pictures, which Thomas already did
questions to ask him: (more questions should be added)
what exactly is he doing (how is he adjusting the machine) when he is at Rheine?
do more farms have the same machine?
what are we not allowed to do with the machine?
what is he currently doing, software wise - current methods - on new machines?
is the machine bad because of hardware or because of software problem?
is he willing to help us to integrate a new software on old machine?
is there a prior integrated?
what is the bucket full behaviour of the machine?
question about demo version - (what didn’t work when Thomas and Sophia went to Rheine last time)
ask him if we can get software QV
thomas, josefine & Sophia feel responsible to prepare slides
Sophia & Michael will hold presentation
split up questions ? - distribute it with asana or before the meeting
maren takes care of coffee & cookies
more precise definition of tasks for the next weeks so that its easier to assign oneself to tasks
get algorithmic baseline - extract features manually
simple python functions: takes an image and extracts thickness / width, rusty, length, color, curvature …
preprocess_images(path, outpath)
extract_width(preprocessed_image, num_measurements = 5): return List_of_Width - Sophia
horizontal_slices(preprocessed_image, num_measurements) begin_end_matrix - Sophia
extract_curvature(preprocessed_image): curvature score - Maren
check_rust(preprocessed_image): score_of_certainty - Michael
check_violet(preprocessed_image): score_of_certainty - Subir
check_flower(preprossed_image): score_of_certainty - Richard, Katha
extract_length(preprocessed_image): length - Malin
human classification - labelling of data
non programming tasks:
classification with hirarchical classes
working with unbalanced classes
semi-supervised learning