novoblake
Computer vision, Depth perception, segmentation, UAV path planning and landing, ML, Control systems, VLSI, Embedded, FPGA
CSIOChandigarh
Pinned Repositories
ai-python-notebooks
Logistic regression, deep learning, YOLO, Recursive Neural Networks, GAN and Conditional GAN
AlgortihmsAndDataStructures
Attention-Graph-Convolution-Network-for-Image-Segmentation-in-Big-SAR-Imagery-Data
the code of paper "Attention Graph Convolution Network for Image Segmentation in Big SAR Imagery Data"
Awesome-Rust-MachineLearning
This repository is a list of machine learning libraries written in Rust. It's a compilation of GitHub repositories, blogs, books, movies, discussions, papers, etc. 🦀
CABiNet
CABiNet: Efficient Context Aggregation Network for Low-Latency Semantic Segmentation (ICRA2021)
ComputerVision
Depth-Anything
[CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation
depthai-viewer
Log images, point clouds, etc, and visualize them effortlessly. Built in Rust using egui
disparity-map
Disparity maps using various algorithms
LooseControl
Lifting ControlNet for Generalized Depth Conditioning
novoblake's Repositories
novoblake/AlgortihmsAndDataStructures
novoblake/Depth-Anything
[CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation
novoblake/LooseControl
Lifting ControlNet for Generalized Depth Conditioning
novoblake/ai-python-notebooks
Logistic regression, deep learning, YOLO, Recursive Neural Networks, GAN and Conditional GAN
novoblake/Awesome-Rust-MachineLearning
This repository is a list of machine learning libraries written in Rust. It's a compilation of GitHub repositories, blogs, books, movies, discussions, papers, etc. 🦀
novoblake/CABiNet
CABiNet: Efficient Context Aggregation Network for Low-Latency Semantic Segmentation (ICRA2021)
novoblake/ComputerVision
novoblake/depthai-viewer
Log images, point clouds, etc, and visualize them effortlessly. Built in Rust using egui
novoblake/euler
A distributed graph deep learning framework.
novoblake/opencv
Open Source Computer Vision Library
novoblake/Robotics
novoblake/Flash
Create, train and deploy AI models without writing code
novoblake/Graph-convolutional-network
convolution operations on graphs, in GCN the convolution operation considers both the node and its neighboring nodes
novoblake/iTPN
(CVPR2023) Integrally Pre-Trained Transformer Pyramid Networks
novoblake/LandUAVSafe-Dataset
LandUAVSafe Dataset : Surface inclination angle estimation using images.
novoblake/multi-object-segmentation
Code for "Multi-Object Discovery by Low-Dimensional Object Motion"
novoblake/nni
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
novoblake/Paper_Writing_Tips
novoblake/PRiMEStereoMatch
A heterogeneous and fully parallel stereo matching algorithm for depth estimation, implementing a local adaptive support weight (ADSW) Guided Image Filter (GIF) cost aggregation stage. Developed in both C++ and OpenCL.
novoblake/PyTorch-High-Res-Stereo-Depth-Estimation
Python scripts form performing stereo depth estimation using the high res stereo model in PyTorch .
novoblake/pytorch_geometric
Graph Library PyTorch
novoblake/Region-adjacency-graph-
RAG , outputs nodes, edges and assocaited weights
novoblake/rocket-chip
Rocket Chip Generator
novoblake/safety_pipeline_UAV
A Lightweight Pipeline for landing obstacles avoidance and safe landing zone extraction
novoblake/segmentation_models
Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
novoblake/stereo-adaptive-weights
stereo with adaptive support weights (Yoon&Kweon, PAMI 2006)
novoblake/SUB-Depth
Official implementation of "SUB-Depth: Self-distillation and Uncertainty Boosting Self-supervised Monocular Depth Estimation" 2021
novoblake/techniques
Techniques for deep learning with satellite & aerial imagery
novoblake/webots
Webots Robot Simulator
novoblake/ZoeDepth
Metric depth estimation from a single image