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ESIPFed / gsoc

Project ideas and mentor guidance for ESIP members to participate in Google Summer of Code.
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Ag-Net: building a customized deep neural network for recognizing crop categories based on spectral characteristics #13

Closed ZihengSun closed 5 years ago

ZihengSun commented 5 years ago

ESIP Member Organization

CSISS/LAITS, George Mason University Alaska Ocean Observing System (AOOS) and Axiom Data Science

Mentors

Ziheng Sun Jesse Lopez

Project Ideas

Ag-Net: building a customized deep neural network for recognizing crop categories based on spectral characteristics

Information for students

See ESIP general guidelines

Abstract

How many kinds of crops can you recognize? It is hard to say many. In most time of growing season, they are all green plants. Dent corn and sweet corn, black bean and red bean, barley and wheat, grass and weeds, etc. Distinguishing them takes a ton of knowledge and experiences. Agriculture scientists have struggled for years to figure out an automated way to recognize them. Deep learning is a powerful tool for non-linear classification problems. The critical part for deep learning is training dataset, which can be extracted from the reports and map products of U.S. department of agriculture. However, the existing deep neural networks are not performing as well as expected on crop classification because of their learned representation features in the back propagation are not common enough to tell the small differences among crops with similar external look. A customized network with special filters may help tell those minor differences in high spectral characteristics for more accurate recognition results.

Technical Details

Python; Keras; Geoweaver; numpy; scikit-learn; matplotlib; GDAL.

Helpful Experience

Machine learning knowledge; satellite image manipulation; python programming.

First steps

Start to get familiar with DeeplabV3, U-net or any other state-of-art deep neural network and test them on a sample training dataset.

CaptainDredge commented 5 years ago

@ZihengSun I've sent the proposal for review on your mail :smile:

1998at commented 5 years ago

@ZihengSun I have Updated The Proposal Added Some Things.Can you please go through it.I understand that at this point you might be flooded with reviewing proposals so make things simpler I have Highlighted Whatever Changes I Made So You wont have to Go through Entire Document.I really Hope That you can Give it One Final Read Before I submit on the portal tomorrow

1998at commented 5 years ago

@ZihengSun Should I give link to the Visualization Notebook Used in the proposal?

1998at commented 5 years ago

@ZihengSun I have submitted My Final Proposal To The GSoC Site After Modifying it according to your Last Feedback.I would Like To Thank You For Helping Me Out With the Proposals.And Will Continue Working On it Trying Various Ways And Communicating With You the results

sankalpmittal1911-BitSian commented 5 years ago

@ZihengSun I have uploaded the final proposal. Please see other sections like training steps where I have delved deeper regarding eliminating overfitting, underfitting etc. Under current approach, I have added reasons why approach is not working and possible steps to eliminate the issues. I hope I have covered mathematically and logically the schedule. Thank you.

ZihengSun commented 5 years ago

Thank you all for your efforts!