Project Blog

Nov 4, 2019

• Performed several experiments with and without context.
• Quantified the results. Results seem to be better with context which helps by giving the context about what the sentence is about.
• Propose some use cases.

Oct 22, 2019

• Trained the model on increased dataset. Tuned the model to improve the accuracy

Oct 8, 2019

• Developed the model and trained on small sample dataset.

Sept 24, 2019

• Developed the flow to extract text and context from images using Google APIs

Sept 10, 2019

• Analyzed the sample dataset collected. Continue collecting the dataset throughout the semester.
• Discussed the implementation techniques
• Model 1 : Use sequence translation model to translate the text in the image.
• Model 2 : Use model to summarize the images.
• For the ambiguous translations in model1 use results from model2 to find the translation with the highest probability.

Sept 3, 2019

• Discussed more about dataset collection for the project.

Aug 27, 2019

• Group meeting to decide timings and discuss CS 298 proposal.

May 6, 2019

• Submitted the project report

Apr 30, 2019

• Cancelled the meeting

Apr 23, 2019

• Discuss Deliverable 4 to extract the dataset

Apr 16, 2019

• Present the paper related to text detection in images
• Discuss Deliverable 3
• Discuss Deliverable 4 to extract the dataset

Apr 9, 2019

• Discussed text extraction techniques
• Discuss Deliverable 3

• Read papers related to text detection/extraction

Mar 26, 2019

• Discussed techniques for image translation (xgettext, .po, .mo files)

Mar 19, 2019

• Discussed the second deliverable

• Finalize the deliverable 2 after doing minor changes
• Read some more papers related to language translation

Mar 12, 2019

• Present the paper on Language translation

• Start text detection from images using openCV libraries

Mar 4, 2019

• Discuss deliverable_2

• Find dataset and start text detection using openCV libraries
• Read a paper on language translation

Feb 26, 2019

• Downloaded images from google to improve dataset. CNN model gave better accuracy for this new dataset

• Improve the dataset for deliverable 1 and do some more experiments
• Update the document for Deliverable 1
• Find relevant papers related to the project and update the document

Feb 19, 2019

• Discussed the deliverable_1 that was developed using both linear regression and CNN and building of dataset with openCV
• Discussed strategies to improve the accuracy for CNN implementation

• Increase the size of dataset
• Print activations at each stage for filters applied
• Print the various filters being applied

Feb 12, 2019

• Decided on sub projects for understanding and building the main project
• Plotted out more concrete deliverables required for 297.

• Start working on deliverable_1 to detect suit and values on playing cards using CNN.
• Decide the platform and libraries for developing the project and also for image transformation for the dataset.
• Develop first cut of this project.

Feb 5, 2019

• Discussed the project in detail
• Discussed about neural networks in general

January 29, 2019

• Decided the project topic
• Decided the meeting day and time for the project to be Tuesday 3.15PM