Dimitris Kastaniotis (@dimkastan)
  • Stars
    star
    193
  • Global Rank 126,672 (Top 5 %)
  • Followers 27
  • Following 71
  • Registered over 10 years ago
  • Most used languages
    Python
    46.2 %
    HTML
    15.4 %
    Lua
    15.4 %
    Cuda
    7.7 %
    MATLAB
    7.7 %
    C++
    7.7 %
  • Location 🇬🇷 Greece
  • Country Total Rank 224
  • Country Ranking
    Cuda
    19
    Lua
    51
    Python
    59
    MATLAB
    152
    HTML
    387
    C++
    648

Top repositories

1

PyTorch-Spectral-clustering

[Under development]- Implementation of various methods for dimensionality reduction and spectral clustering implemented with Pytorch
Python
158
star
2

ATA-GAN

Demo code for Attention-Aware Generative Adversarial Networks paper
Python
12
star
3

sift-cnn-all-sky-images

Python
5
star
4

RaccoonsVsCats

Train a Deep CNN using images acquired automatically from google search with Selenium
Python
3
star
5

PythonUtilsForCaffe

Some very useful Python utilities for manipulating lmdb files for Caffe (append lmdb, inspect entries, etc)
Python
2
star
6

dimkastan.github.io

GitHub Personal web site https://dimkastan.github.io/
HTML
1
star
7

Torch-Train-on-food-dataset

Training a Deep neural network with torch- Application on food recognition
Lua
1
star
8

CreateCaffeProtFromPython

Examples for creating caffe prototxt models using Python
1
star
9

STEM_MachineLearningClass

Interdisciplinary Approach to Science, Technology, Engineering and Mathematics - STEM in Education- Lectures site
HTML
1
star
10

TorchDemos

Some torch demos based on official torch examples with some extra features
Lua
1
star
11

websocket_tutorials

Python
1
star
12

OpenCV_examples

Some simple but very usefull OpenCV examples
C++
1
star
13

CudaViaCmake

This is a very simple project using CMake in order to create a project for compiling cuda with cpp code.
Cuda
1
star
14

LipReadingGreekWords

Repository for the paper "Lip Reading in unconstrained driving scenario with Greek words"
1
star
15

ORLandVLAD

Simple demonstration of the VLAD method for creating mid-level image representation for face recognition
MATLAB
1
star