Name: Alborz
Type: User
Company: Samsung AI Research Centre
Bio: I am an AI research scientist, interested in computer vision, human-computer interaction, machine learning and brain-computer interfaces.
Location: Toronto, Canada
Alborz's Projects
Python solution to the assignments of the Algorithm course (Stanford University) in Coursera.
Pytorch code for the IEEE TM/ECCV paper "Attend and rectify"
Implementing Attention Augmented Convolutional Networks using Pytorch
Official PyTorch code for "BAM: Bottleneck Attention Module (BMVC2018)" and "CBAM: Convolutional Block Attention Module (ECCV2018)"
This library contains cross validation and test set classification codes written in MATLAB.
FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.
Feature extraction (autoregressive and wavelet transform features) and epoching (from vhdr files and using marker) codes in MATLAB for analyzing EEG (electroencephalography) data for brain-computer interfaces (BCIs).
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
Preprocessing and feature extraction (slopes, moving slopes, Kurtosis, skewness, mean and variance) codes in MATLAB for analyzing fNIRS (functional near-infrared spectroscopy) data for brain-computer interfaces (BCIs).
Keras implementation of RetinaNet object detection.
Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.
Open MMLab Detection Toolbox and Benchmark
Some Python codes for training and testing various types of neural networks
Python solution to some of the problems listed in https://projecteuler.net
Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet)
PyTorch implementation of Grad-CAM
PyTorch implementation of SENet
Implementing Stand-Alone Self-Attention in Vision Models using Pytorch
KDD 2020 Workshop