Entity identification using machine learning
US-2021142052-A1 · May 13, 2021 · US
US11297806B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11297806-B2 |
| Application number | US-202016743023-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jan 15, 2020 |
| Priority date | Jan 15, 2020 |
| Publication date | Apr 12, 2022 |
| Grant date | Apr 12, 2022 |
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Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for a lighting controller for sea lice detection. In some implementations, a pulse of red light and a pulse of blue light can be timed with the exposure of a camera to capture multiple images of a fish or group of fishes in both red and blue light. By using the captured images with different color light, computers can detect features on the body of a fish including sea lice, skin lesions, shortened operculum or other physical deformities and skin features. Detection results can aid in mitigation techniques or be stored for analytics. For example, sea lice detection results can inform targeted treatments comprised of lasers, fluids, or mechanical devices such as a brush or suction.
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What is claimed is: 1. A computer-implemented method comprising: illuminating a particular fish with pairs of discrete light pulses that are separated by time and that each include a pulse of red light and a pulse of blue light; controlling an exposure of a camera to (i) generate a first image of the particular fish during a pulse of one of the red light or the blue light during an initial pair of the light pulses, (ii) not generate an image during a pulse an other of the red light or the blue light during the initial pair of the light pulses as well as during one or more succeeding pairs of the light pulses, and (iii) generate a second image of the particular fish during a pulse of the other of the red light or the blue light during a subsequent pair of the light pulses; and determining whether the particular fish is likely affected by a particular condition based on an analysis of at least the first image and the second image. 2. The computer-implemented method of claim 1 , wherein the particular condition comprises a sea lice infection, an occurrence of a lesion, or a physical deformity. 3. The computer-implemented method of claim 1 , wherein the particular fish is contained within a fish pen or a fish run. 4. The computer-implemented method of claim 1 , wherein the pairs of the light pulses each comprise the pulse of blue light with peak power within a wavelength range of 450 nanometers to 480 nanometers. 5. The computer-implemented method of claim 1 , wherein the pairs of the light pulses feature an alternating rate of greater than 60 Hz. 6. The computer-implemented method of claim 1 , wherein generating each image comprises: exposing a camera device for at least a portion of a time interval between a start of a particular light pulse and an end of the particular light pulse to capture exposure data; or exposing a camera device for at least a portion of a time interval between the end of the particular light pulse and a start of a succeeding light pulse to capture exposure data. 7. The computer-implemented method of claim 1 , wherein the light pulses within each pair of the light pulses are activated in discrete time intervals and do not overlap. 8. The computer-implemented method of claim 1 , wherein machine learning informs illuminating the particular fish or generating the images of the particular. 9. The computer-implemented method of claim 1 , wherein machine learning informs sea lice detection on the particular fish. 10. The computer-implemented method of claim 1 , comprising storing the generated images in an image buffer. 11. A computer-implemented method comprising: illuminating a particular fish with pairs of discrete light pulses that are separated by time and that each include a pulse of red light and a pulse of blue light; controlling an exposure of a camera to (i) generate a first image of the particular fish during a pulse of one of the red light or the blue light during an initial pair of the light pulses, (ii) generate a second image of the particular fish during a pulse of an other of the red light or the blue color of light during the initial pair of the light pulses, (iii) and not generate an image during one or more succeeding pairs of the light pulses; and determining whether the particular fish is likely affected by a particular condition based on an analysis of at least the first image and the second image. 12. The computer-implemented method of claim 11 , wherein the particular condition comprises a sea lice infection, an occurrence of a lesion, or a physical deformity. 13. The computer-implemented method of claim 11 , wherein the pairs of the light pulses each comprise the pulse of blue light with peak power within a wavelength range of 450 nanometers to 480 nanometers. 14. The computer-implemented method of claim 11 , wherein the pairs of the light pulses feature an alternating rate of greater than 60 Hz. 15. The computer-implemented method of claim 11 , wherein generating each image comprises: exposing a camera device for at least a portion of a time interval between a start of a particular light pulse and an end of the particular light pulse to capture exposure data; or exposing a camera device for at least a portion of a time interval between the end of the particular light pulse and a start of a succeeding light pulse to capture exposure data. 16. A computer-implemented method comprising: illuminating a particular fish with pairs of discrete light pulses that are separated by time and that each include a pulse of red light and a pulse of blue light; controlling an exposure of a camera to (i) generate a first image of the particular fish during a pulse of one of the red light or the blue light during an initial pair of the light pulses, (ii) not generate an image during a pulse of an other of the red light or the blue light during the initial pair of the light pulses as well as during a pulse of the one of the red light or the blue light during a succeeding pair of the light pulses, (iii) generate a second image of the particular fish during a pulse of the other of the red light or the blue light during the succeeding pair of the light pulses, (iv) not generate an image during a pulse of the one of the red light or the blue light during a subsequent pair of the light pulses as well as during a pulse of the other of the red light or the blue light during the subsequent pair of the light pulses, and (v) generate a third image of the particular fish after the subsequent pair of the light pulses but before a further pair of the light pulses; and determining whether the particular fish is likely affected by a particular condition based on an analysis of at least the first image and the second image. 17. The computer-implemented method of claim 16 , wherein the particular condition comprises a sea lice infection, an occurrence of a lesion, or a physical deformity. 18. The computer-implemented method of claim 16 , wherein the pairs of the light pulses each comprise the pulse of blue light with peak power within a wavelength range of 450 nanometers to 480 nanometers. 19. The computer-implemented method of claim 16 , wherein the pairs of the light pulses feature an alternating rate of greater than 60 Hz. 20. The computer-implemented method of claim 16 , wherein generating each image comprises: exposing a camera device for at least a portion of a time interval between a start of a particular light pulse and an end of the particular light pulse to capture exposure data; or exposing a camera device for at least a portion of a time interval between the end of the particular light pulse and a start of a succeeding light pulse to capture exposure data.
provided with illuminating means · CPC title
Arrangements for heating or lighting in, or attached to, receptacles for live fish · CPC title
Prevention or treatment of fish diseases · CPC title
Electricity · mapped topic
Aquaculture, e.g. of fish · CPC title
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