Comments (3)
As the code shows, the loss is "mean squared error", which is the mean of squared difference between input and output.
If you want to write your own loss function, please follow KERAS documentation on "Creating custom losses" here --> https://keras.io/api/losses/.
from fall-detection.
but as the paper said,the loss formula is as follow:
I want to know where the code is?
from fall-detection.
This is not the formula for loss, rather it is to calculate the anomaly score. You will want to look into util.py and the following functions below.
def make_cross_window_matrix(scores):
def agg_window(RE, agg_type):
def gather_auc_avg_per_tol(inwin_mean, inwin_std, labels, win_len = 8):
from fall-detection.
Related Issues (13)
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from fall-detection.