SeamOCR 

SeamOCR is an ongoing project aimed at streamlining digital invoice processing through advanced image and OCR technologies. The project involves two main components: an image processing engine and an OCR engine, working together to convert invoice images into machine-readable text

Role: Focused on Image Processing Model Optimizing
Technologies Used: OpenCV, PyTesseract

Responsibilities:

• Fine-tuned the image processing model to enhance OCR (Optical Character Recognition) results significantly.

• Standardized parameter ratios, achieving a 65% improvement in OCR accuracy, thereby enhancing the reliability and efficiency of invoice processing systems.

FDE Scraper 

The FDE Scraper project focuses on the continuous collection, cleaning, and storage of financial data from 600 different websites, covering 5000 financial funds. This data is essential for providing up-to-date financial insights to clients.

 
Role: Data Cleaning and Management
Technologies Used: SQL, Various NLP Technologies
Project Description:

Responsibilities:

• Played a key role in the data cleaning process for a large-scale financial data scraping project.

• Utilized advanced SQL and NLP techniques, including lemmatization, to preprocess and refine data collected from 600 websites encompassing 5000 financial funds.

• Ensured accurate and clean data storage, facilitating efficient data retrieval and usage for client-specific applications.

SeamOCR 

SeamOCR is an ongoing project aimed at streamlining digital invoice processing through advanced image and OCR technologies. The project involves two main components: an image processing engine and an OCR engine, working together to convert invoice images into machine-readable text

Role: Focused on Image Processing Model Optimizing
Technologies Used: OpenCV, PyTesseract

Responsibilities:

• Fine-tuned the image processing model to enhance OCR (Optical Character Recognition) results significantly.

• Standardized parameter ratios, achieving a 65% improvement in OCR accuracy, thereby enhancing the reliability and efficiency of invoice processing systems.

FDE Scraper 

The FDE Scraper project focuses on the continuous collection, cleaning, and storage of financial data from 600 different websites, covering 5000 financial funds. This data is essential for providing up-to-date financial insights to clients.

 
Role: Data Cleaning and Management
Technologies Used: SQL, Various NLP Technologies
Project Description:

Responsibilities:

• Played a key role in the data cleaning process for a large-scale financial data scraping project.

• Utilized advanced SQL and NLP techniques, including lemmatization, to preprocess and refine data collected from 600 websites encompassing 5000 financial funds.

• Ensured accurate and clean data storage, facilitating efficient data retrieval and usage for client-specific applications.

Sign to Speech

Sign to Speech is a project aimed at improving communications with mute and deaf people. Converts sign language to sign and then to speech by text to speech (TTS) technology. 

Responsibilities:

• Designed OpenCV based system to capture signs, Train the model to achieve accuracy.

• Finetuned NLP with RAG to form accurate sentences from letters obtained through Sign language.

• Used TTS for further converting sentences to speech.

Technologies Utilized: Computer Vision, TTS, Lama 2, RAG, SQL, Python 

Sign to Speech

Sign to Speech is a project aimed at improving communications with mute and deaf people. Converts sign language to sign and then to speech by text to speech (TTS) technology. 

Responsibilities:

• Designed OpenCV based system to capture signs, Train the model to achieve accuracy.

• Finetuned NLP with RAG to form accurate sentences from letters obtained through Sign language.

• Used TTS for further converting sentences to speech.

Technologies Utilized: Computer Vision, TTS, Lama 2, RAG, SQL, Python