munjalbharti Goto Github PK
Name: Bharti
Type: User
Company: TU Munich
Location: Germany
Name: Bharti
Type: User
Company: TU Munich
Location: Germany
This project was done as part of Camelyon16 challenge (http://camelyon16.grand-challenge.org/home/) . Details of this work can be found here: https://www.dropbox.com/s/8yhq7bq57n1v317/Cancer_Metastasis.pdf?dl=0 and https://www.dropbox.com/s/gk50i9zorua6kyj/Cancer_Metastasis_Report.pdf?dl=0
source code to ICLR'19, 'A Closer Look at Few-shot Classification'
ICCV2017 The Person re-ID Evaluation Code for DukeMTMC-reID Dataset (Including Dataset Download)
ID-discriminative Embedding (IDE) for Person Re-identification
Rethinking the Inception Architecture for Computer Vision
This project was done as part of seminar IN4804 ( https://campus.tum.de/tumonline/wblv.wbShowLvDetail?pStpSpNr=950185220&pSpracheNr=1&pMUISuche=FALSE). The project aims to detect lanes using camera inputs for autonomous driving.
Models and examples built with TensorFlow
This work was done as part of my thesis at Technical University of Munich. The goal of this thesis was to do object detection using Fully Convolutional Network. Full Report of this work can be found here: https://www.dropbox.com/s/hq5y2vxqo0r0ddn/ObjectDetectionThesisReport.pdf?dl=0
Open source person re-identification library in python
Pytorch implement of Person re-identification baseline. We arrived Rank@1=88.24%, mAP=70.68% only with softmax loss. Re-ranking is added.
Joint Detection and Identification Feature Learning for Person Search
Vision based target navigation for Parrot AR DRONE. Uses epipolar geometry methods to compute the target position of the quadcopter based on the current location and target image provided.
Implementation of triplet loss in TensorFlow
These assignments were done as part of practical IN4174 (https://campus.tum.de/tumonline/wblv.wbShowLvDetail?pStpSpNr=950246448&pSpracheNr=2&pMUISuche=FALSE)
This was done for a data mining competition at Kaggle (https://www.kaggle.com/c/predict-west-nile-virus). Final rank was 385 out of 1300 participants.
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