This repo contains computer vision projects with pytorch

Fine-tune Facebook's DETR (DEtection TRansformer) on Colaboratory.

Segmentation of aerial images using two approaches: 1) texture features, 2) vegetation index

Food calorie estimations Using Deep Learning And Computer Vision

A repository for the computer vision team in BYU's record linking lab

UI of Detection and Segmentation in Powder Spreading Process of Magnetic Material Additive Manufacturing.

[BMVC 2022] SearchTrack: Multiple Object Tracking with Object-Customized Search and Motion-Aware Features

This is a data analysis portfolio project that will allow understand to performance of customers based on segmentation of mall customers

# Using technology of computer vision to classify clouds.

Bank Customer Segmentation and Insurance Claim Prediction - The project involved drawing inferences from 2 case studies, namely - Bank Marketing & Insurance. The concepts of Clustering, CART, Random Forest, Artificial Neural Network are used to draw inferences from these case studies. Various performance metrics have been used to validate the performance of predictions on Test & Train sets. Skills and Tools Clustering, CART, Random Forest, Artificial Neural Networks.

Use case: A portable and automated workflow, to be run on demand. Functionalities: Workflow extracted and read data from a given SQL server instance. Prompt input for location of Excel file to write on. Segmentation and aggregations, given conditions. Ran a developed macro in VBA, verifying the workflow output.

My take on card localization and classification

My Data Science Degree Capstone Project

:hospital: 医学图像作业：图像配准论文阅读；眼底血管分割实验

Collection of Object Detection and Segmentation Pipelines🛸🚀

Recognize scanned sheets and convert them into Excel sheet

The purpose of this repository is to provide good insight to the Pytorch practitioner, especially for the newbie.

Predict the type and localise the defect using Image Segmentation

🚥 SegmentSwitchTab

Baidu Tieba spider, word segmentation and wordcloud

Implementation of U_Net architecture for medical image segmentation purpose.

A deep learning approach to fight COVID virus. This model uses CNN with transfer learning to detect if a person is infected with COVID by looking at the lung X-Ray and further it segments the infected region of lungs producing a mask using U-Net

HVSMR 2016: MICCAI Workshop on Whole-Heart and Great Vessel Segmentation from 3D Cardiovascular MRI in Congenital Heart Disease

A collection of scripts to create an audio data-set with energy based segmentation.

Was hacking around with the KITTI dataset to create an encoder-decoder CNN for road segementation.

MATLAB implementation to segment breast lesions in ultrasound images (ICIAR 2016)

Marketing in a Digital World - Implications of Internet Core Trends for TV Advertising

A Predictive Analysis of H1B Dataset using both supervised and unsupervised learning