Rushikesh Darge 's Projects
Boundary Patch Refinement (BPR) is a post-processing that improves the quality of instance segmentation boundaries. It involves extracting and refining small boundary patches along the predicted instance boundaries.
Dataset of is a leaf is infected by disease or not
This project outlines the development of a comprehensive ETL (Extract, Transform, Load) pipeline leveraging AWS services to streamline data processing and unlock valuable insights. The pipeline will extract data from various sources, transform it for efficient analysis, and load it into a readily accessible format for visualization.
GEETA GPT is an advanced AI application built using Retrieval-Augmented Generation (RAG). It leverages the powerful capabilities of the Large Language Models to provide insightful and accurate responses based on the rich content of the Bhagavad Gita.
The Human Activity Recognition database was built from the recordings of 30 study participants performing activities of daily living (ADL) while carrying a waist-mounted smartphone with embedded inertial sensors. The objective is to classify activities into one of the six activities performed.
Text documents are one of the richest sources of data for businesses: whether in the shape of customer support tickets, emails, technical documents, user reviews or news articles, they all contain valuable information that can be used to automate slow manual processes, better understand users, or find valuable insights. However, traditional algorithms struggle at processing these unstructured documents, and this is where machine learning comes to the rescue!
Writing machine learning algorithms from scratch without using sklearn library
Digit recognition system is the working of a machine to train itself or recognizing the digits from different sources like emails, bank cheque, papers, images, etc. and in different real-world scenarios for online handwriting recognition on computer tablets or system, recognize number plates of vehicles, processing bank cheque amounts, numeric entries in forms filled up by hand (say — tax forms,receipts) and so on. Our goal is to create a system which detects numbers from images based on previously learned datasets.
Attention base Model to translate english text to hindi text. Attention models, also called attention mechanisms, are deep learning techniques used to provide an additional focus on a specific component. In deep learning, attention relates to focus on something in particular and note its specific importance.
Olist is an Small and Midsize Business (SMB) commerce enabler ecosystem that specializes in the fields of logistics and capital. Commerce has changed and platforms like shopify, amazon, meli, alibaba and their peers are more and more relevant to our economy throughout the globe. This movement triggered a new generation of enablers to support small businesses navigate in suchrich and fragmented ecosystem. Olist is leading the way as the #1 commerce enabler for SMBs in Brazil, now expanding globally.
This project utilizes the YOLO (You Only Look Once) object detection algorithm combined with the ByteTrack multi-object tracking algorithm to monitor and count people passing a specified marker. The direction of movement (right-to-left or left-to-right) is recorded, and counters are incremented accordingly.
Over 100 million people visit Quora every month, so it's no surprise that many people ask similarly worded questions. Multiple questions with the same intent can cause seekers to spend more time finding the best answer to their question, and make writers feel they need to answer multiple versions of the same question. Quora values canonical questions because they provide a better experience to active seekers and writers, and offer more value to both of these groups in the long term.
Config files for my GitHub profile.
Nowadays on social networks where everyone can upload whatever they want without having to count that there might be children watching that or people don't want to watch that. To avoid this we need to come up with a solution that filters based real-time and with high accuracy using chrome extension that filters real-time NSFW (not safe for working) images and replaces them with SFW (safe for working) images.
San Francisco Airport Visualization
Tableau Sales insight Project
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent