RSS Feed - Blog
About: In DMNS source, five databases are used in slover.cpp and data_veh_layer.cpp, these images and databases are included in this file, except munich database. Changes:Initial Announcement on mloss.org.
|
About: Deep measuring net sequence(DMNS) is a sequence of three deep measuring nets, the later are deep fcn-based networks, directely output object category score, object orientation, location and scale simultaneously without any anchor boxes. DMNS acheived high accuracy in maneuvering target detection and geometrical measurements. Its average orientation error is less than 3.5 degree, loaction error less than 1.3 pixel, scale measuring error less than 10%, achieve a detection F1-score 96.5% in OAD, 91.8% in SVDS ,90.8% in Munich , 87.3% in OIRDS, outperforms SSD, Fater R-CNN, etc. Changes:Initial Announcement on mloss.org.
|
About: This database include 164 satellite iamges of different airports from google-earth, the first 110 images are used as training images, include 2337 aircrafts, the remained 54 images are used as test images, include 2206 aircrafts, each aircraft are labeled by two points and one number, indicating the positions of head and tail,and which point is the head. The labeled informations are recorded in two files: train.txt and test.txt, matlab is recommanded to be used for reading these data by import data tool. Changes:Initial Announcement on mloss.org.
|
About: The scancity of open database of small targets in remotesensing field has hindered the research in a lot. This open database includes 111 satellite images from google earth, 80 images are used as training set, contains 7862 vehicles. The other 31 images sre used as test set, contains 1635 vehicles. The positions of each vehicle are labeled by two points, which are recorded in "train.txt" and "test.txt" respectively. The label information is easily to be read by matlab tool. So such an open database is very useful for researchers in object detection fields. Changes:Initial Announcement on mloss.org.
|
About: a tool for marking samples in images for database building, also including algorithm of LBP,HOG,and classifiers of SVM (six kernels), adaboost,BP and convolutional networks, extreme learning machine. Changes:Initial Announcement on mloss.org.
|
|