Patent ID: 11925173
Assignee: OBSERVE TECHNOLOGIES LIMITED
Field: Computer technology (Electrical engineering)
Classification: CPC A  G  Y | IPC A  G

Claim 13:
14. The method of claim 13, wherein the optimised level of feed is generated through the use of the one or more neural networks to form a model;
optionally wherein the one or more neural networks comprise one or more convolutional neural networks (CNNs); and/or
optionally wherein the model is trained and formed to: analyse real time image data to perform feed detection and localisation; analyse previous image frames to identify movement and/or warping of pellets relative to current real time image data frames; and enhance the distinction of feed and waste for future image frames; and/or
further optionally wherein localization is performed using one or more blob detectors; and/or
still further optionally wherein the one or more neural networks uses the one or more feedback loops to provide the temporal information: optionally wherein the one or more neural networks comprises any of: Long Short Term Memory (LSTM) neural networks; Recurrent neural networks (RNN); Gated Recurrent Unit (GRU); internal state machines; and/or circular buffers; and/or
further optionally wherein the one or more neural networks is used to create a feature set from the sensor data by correlating two or more feature signals obtained from the sensor data; and/or
further optionally the method comprising determining, from a portion of stored data, at least one new parameter for deriving the amount of feed using a deep learning (DL) algorithm; and/or
further optionally wherein the model is arranged to continuously learn in real time.