Pinned Repositories
aimet-model-zoo
anonymous_github
Anonymous Github is a proxy server to support anonymous browsing of Github repositories for open-science code and data.
attention-transfer
Improving Convolutional Networks via Attention Transfer (ICLR 2017)
Auto-GPT
An experimental open-source attempt to make GPT-4 fully autonomous.
Hands-On-Meta-Learning-With-Python
Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow
Map-based-Visual-Localization
A general framework for map-based visual localization. It contains 1) Map Generation which support traditional features or deeplearning features. 2) Hierarchical-Localizationvisual in visual(points or line) map. 3)Fusion framework with IMU, wheel odom and GPS sensors.
milliEgo
OpenRadar
An open source library for interacting with and processing radar data, specialized for MIMO mmWave radars
PDR-with-Map-Matching
A solution for indoor positioning. Based on PDR. With map matching. Using chest mounted IMU. Got 1st place in IPIN 2017 competition Track 2. Got 2nd place in IPIN 2018 competition Track 2 (0.2m worse than 1st).
pytorch-weights_pruning
PyTorch Implementation of Weights Pruning
Zber5's Repositories
Zber5/Hands-On-Meta-Learning-With-Python
Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow
Zber5/Map-based-Visual-Localization
A general framework for map-based visual localization. It contains 1) Map Generation which support traditional features or deeplearning features. 2) Hierarchical-Localizationvisual in visual(points or line) map. 3)Fusion framework with IMU, wheel odom and GPS sensors.
Zber5/pytorch-weights_pruning
PyTorch Implementation of Weights Pruning
Zber5/AWR1843-Read-Data-Python-MMWAVE-SDK-3-
Python program to read and plot the data in real time from the AWR1843 mmWave radar board (MMWAVE SDK 3)
Zber5/examples
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
Zber5/fmcw-RADAR
[mmWave based fmcw radar design files] based on AWR1843 chip operating at 76-GHz to 81-GHz.
Zber5/FMPN-FER
Official PyTorch Implementation of 'Facial Motion Prior Networks for Facial Expression Recognition', VCIP 2019, Oral
Zber5/FSensor
Android Sensor Filter and Fusion
Zber5/hands-on-transfer-learning-with-python
Deep learning simplified by transferring prior learning using the Python deep learning ecosystem
Zber5/LearnablePINs
An attempt to replicate the results of [1805.00833] Learnable PINs: Cross-Modal Embeddings for Person Identity
Zber5/LearningToCompare_FSL
PyTorch code for CVPR 2018 paper: Learning to Compare: Relation Network for Few-Shot Learning (Few-Shot Learning part)
Zber5/LearnToPayAttention
PyTorch implementation of ICLR 2018 paper Learn To Pay Attention (and some modification)
Zber5/machine-learning-mindmap
A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.
Zber5/MAML-Pytorch
Elegant PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML)
Zber5/mmWave_gesture_iwr6843
Zber5/MobileBert_PyTorch
MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices
Zber5/morph-net
Fast & Simple Resource-Constrained Learning of Deep Network Structure
Zber5/Multi-label-Classification
Multi-label Classification using feature selection: Deep Learning
Zber5/Prototypical-Networks-for-Few-shot-Learning-PyTorch
Implementation of Prototypical Networks for Few Shot Learning (https://arxiv.org/abs/1703.05175) in Pytorch
Zber5/pychirpz
Python and C++ implementation of the Chirp-Z transform
Zber5/pymmw
Pythonic mmWave Toolbox for TI's IWR Radar Sensors
Zber5/pytorch-cnn-visualizations
Pytorch implementation of convolutional neural network visualization techniques
Zber5/pytorch-maml
An Implementation of Model-Agnostic Meta-Learning in PyTorch with Torchmeta
Zber5/pytorch-meta
A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
Zber5/pytorch-pruning
PyTorch Implementation of [1611.06440] Pruning Convolutional Neural Networks for Resource Efficient Inference
Zber5/RingNet
Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision
Zber5/seq2seq
PyTorch implementation of the RNN-based sequence-to-sequence architecture.
Zber5/stylegan-encoder
StyleGAN Encoder - converts real images to latent space
Zber5/tutorials
PyTorch tutorials.
Zber5/xizhang.github.io