Anmol Sharma (@trane293)
  • Stars
    star
    92
  • Global Rank 220,720 (Top 8 %)
  • Followers 17
  • Registered almost 10 years ago
  • Most used languages
    MATLAB
    33.3 %
    C++
    22.2 %
    Python
    22.2 %
    HTML
    11.1 %
    C
    11.1 %
  • Location 🇨🇦 Canada
  • Country Total Rank 5,914
  • Country Ranking
    MATLAB
    44
    C
    1,096
    C++
    1,374
    Python
    4,014
    HTML
    4,307

Top repositories

1

DDSMUtility

Utility to greatly simplify downloading, converting, viewing and extracting annotations from the Digital Database for Screening Mammography (DDSM) database available here: http://marathon.csee.usf.edu/Mammography/Database.html
MATLAB
54
star
2

mm-gan

Python
12
star
3

Object-Detection-Framework-Using-HOG-And-SVM

The project aims to provide a generic framework which utilized HOG as features and SVM as classifier to detect any objects that the user wants. The classifier can be trained to detect to detect anything. Just add positive images to pos folder and negative images to neg folder.
C
10
star
4

Palm-Fist-Gesture-Recognition

The repository contains two trained Haar cascades for palm and fist gesture detection. The code is the underlying base for a bigger project which will utilize these gestures for a smart application. The project will be based on C++ and OpenCV
C++
6
star
5

Real-Time-Face-Detection-OpenCV-GPU

C++
5
star
6

trane293.github.io

Personal Webpage
HTML
2
star
7

dicom-converter

Automatically read, infer sequences, resample and convert DICOM images exported from Vancouver General Hospital.
Python
1
star
8

DDSM-Software-Chris-Rose

This is a mirror repository for hosting the important DDSM Software written by Dr. Chris Rose, University of Manchester. This is just in case when the official website (microserf.org.uk) is down.
MATLAB
1
star
9

Handwritten-Digit-Classification

Developed a framework to recognize handwritten digits (0-9) using image moments as shape descriptors and a feed forward artificial neural network as classifier. It was implemented to test the recognition power of orthogonal moments.
MATLAB
1
star