Python GraphFPN-Graph-Feature-Pyramid-Network-for-Object-Detection Resources

Brain-Tumor-Detection Building a detection model using a convolutional neural network in Tensorflow & Keras. Used brain MRI images. InceptionResNetV2

Speech Recognition is an important feature in several applications used such as home automation, artificial intelligence, etc. This article aims to provide an introduction on how to make use of the SpeechRecognition and pyttsx3 library of Python.

Using Opencv ,this project is based on Augmental Reality(AR) and will show the feature matching of image and then by finding its matching ,it will just mask that image . This project ,if used in cctv then it will detect black listed people if mentioned properly with their images.

TTS-GAN: A Transformer-based Time-Series Generative Adversarial Network This repository contains code from the paper "TTS-GAN: A Transformer-based Tim

TGIN Tensorflow implementation of our method: "Triangle Graph Interest Network for Click-through Rate Prediction". Files in the folder dataset/ electr

MarkovGNN This is the official PyTorch-Geometric implementation of MarkovGNN paper under the title "MarkovGNN: Graph Neural Networks on Markov Diffusi

TorchMD-net TorchMD-Net provides state-of-the-art graph neural networks and equivariant transformer neural networks potentials for learning molecular

Transfer-Learning-in-Reinforcement-Learning Transfer Reinforcement Learning for Differing Action Spaces via Q-Network Representations Final Report Tra

OMLT is a Python package for representing machine learning models (neural networks and gradient-boosted trees) within the Pyomo optimization environment.

Edge-Selective Feature Weaving for Point Cloud Matching This repository contains a PyTorch-lightning implementation of the ESFW module proposed in our

Feature-Style Encoder for Style-Based GAN Inversion Official implementation for paper: Feature-Style Encoder for Style-Based GAN Inversion. Code will

BlackIP-Rep is a tool designed to gather the reputation and information of Bulk IP's. Focused on increasing the workflow of Security Operations(SOC) team during investigation.

Real-time Instance Segmentation and Lane Detection This is a lane detection integrated Real-time Instance Segmentation based on YOLACT (You Only Look

Simple-Face-Detection This code uses OpenCV and Python Code to detect a face on the screen. This serves as an example program. Important prerequisites

EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein

Large-Scale Unsupervised Object Discovery Huy V. Vo, Elena Sizikova, Cordelia Schmid, Patrick Pérez, Jean Ponce [PDF] We propose a novel ranking-based

FILM: Frame Interpolation for Large Scene Motion Project | Paper | YouTube | Benchmark Scores Tensorflow 2 implementation of our high quality frame in

Julia package for contraction of tensor networks, based on the sweep line algorithm outlined in the paper General tensor network decoding of 2D Pauli codes

Code for CCA-SSG model proposed in the NeurIPS 2021 paper From Canonical Correlation Analysis to Self-supervised Graph Neural Networks.

HGCN The official repo of "HGCN: Harmonic Gated Compensation Network For Speech Enhancement", which was accepted at ICASSP2022. How to use step1: Calc

Causal Influence Detection for Improving Efficiency in Reinforcement Learning This repository contains the code release for the paper "Causal Influenc

M3DSSD: Monocular 3D Single Stage Object Detector Setup pytorch 0.4.1 Preparation Download the full KITTI detection dataset. Then place a softlink (or

DDMP-3D Pytorch implementation of Depth-conditioned Dynamic Message Propagation forMonocular 3D Object Detection, a paper on CVPR2021. Instroduction T

Monocular 3D Object Detection: An Extrinsic Parameter Free Approach (CVPR2021) Yunsong Zhou, Yuan He, Hongzi Zhu, Cheng Wang, Hongyang Li, Qinhong Jia

PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection? (ICCV 2021), Dennis Park*, Rares Ambrus*, Vitor Guizilini, Jie Li, and Adrien Gaidon.

MonoRCNN MonoRCNN is a monocular 3D object detection method for automonous driving, published at ICCV 2021. This project is an implementation of MonoR

Awesome Monocular 3D detection Paper list of 3D detetction, keep updating! Contents Paper List 2022 2021 2020 2019 2018 2017 2016 KITTI Results Paper

Convolutional Neural Network to detect deforestation in the Amazon Rainforest This project is part of my final work as an Aerospace Engineering studen

SST Coursework 2022 About the app A python application that utilises the tensorflow object detection algorithm to achieve automatic detection of ameri

The project has set itself the goal of analyzing the thoughts and interaction of Italian users through the social posts expressed through the Twitter platform on the day of the entry into force of the new measures. In particular, we want to research the reference hubs present on the network, but also the sentiment and emotions of peoples with respect to the new limitations.

UMPNet: Universal Manipulation Policy Network for Articulated Objects Zhenjia Xu, Zhanpeng He, Shuran Song Columbia University Robotics and Automation

Disclaimer This tool is for Educational purpose only. We do not promote or encourage any illegal activities. Summary These are Simple python scripts t

PacketPy About PacketPy is an open-source solution for stress testing network devices using different testing methods. Currently, there are only two c

Energy_Output_Predictor Artificial Neural network regression model to predict the energy output in a combined cycle power plant. Abstract Energy outpu

Create a semantic search engine with a neural network (i.e. BERT) whose knowledge base can be updated. This engine can later be used for downstream tasks in NLP such as Q&A, summarization, generation, and natural language understanding (NLU).

A python scripts that uses 3 different feature extraction methods such as SIFT, SURF and ORB to find a book in a video clip and project trailer of a movie based on that book, on to it.

Large-scale Knowledge Graph Construction with Prompting across tasks (predictive and generative), and modalities (language, image, vision + language, etc.)

LicensePlate_Project 🚗 🚙 [Project] 2021.02 ~ 2021.09 License Plate Detection Application Overview 1. 데이터 수집 및 라벨링 차량 번호판 이미지를 직접 수집하여 각 이미지에 대해 '번호판

FIRA is a learning-based commit message generation approach, which first represents code changes via fine-grained graphs and then learns to generate commit messages automatically.

This library attempts to abstract the handling of Sigma rules in Python. The rules are parsed using a schema defined with pydantic, and can be easily loaded from YAML files into a structured Python object.

BoxPlotGraphAutomation Automatization of BoxPlot graph usin Python / Excel. This file is an automation of BoxPlot-Graph using python graph library mat

A Graph Learning library for Humans These novel algorithms include but are not limited to: A graph construction and graph searching class can be found

obj-encrypt is an encryption library based on the AES-256 algorithm. It uses Python objects as the basic unit, which can convert objects into binary ciphertext and support decryption. Objects encrypted with obj-encrypt support TCP communication, database storage, and more.

HAIS_2GNN: 3D Visual Grounding with Graph and Attention This repository is for the HAIS_2GNN research project. Tao Gu, Yue Chen Introduction The motiv

A tool to get a minimalist view of any architecture This tool has only be tested with the models included in this repo. Therefore, I can't guarantee t

Multi-Stage Spatial-Temporal Convolutional Neural Network (MS-GCN) This code implements the skeleton-based action segmentation MS-GCN model from Autom

This is the repository for codes for ML, domain generation, graph generation of Asymmetric Buckling Columns (ABC) dataset in the paper "Learning Mechanically Driven Emergent Behavior with Message Passing Neural Networks".

SBINN: Systems-biology informed neural network The source code for the paper M. Daneker, Z. Zhang, G. E. Karniadakis, & L. Lu. Systems biology: Identi

Graph Coloring - Weighted Vertex Coloring Problem This project proposes several local searches and an MCTS algorithm for the weighted vertex coloring

TONet Introduction The official implementation of "TONet: Tone-Octave Network for Singing Melody Extraction from Polyphonic Music", in ICASSP 2022 We

Code Impementation for "Mold into a Graph: Efficient Bayesian Optimization over Mixed Spaces" This repo contains the implementation of GEBO algorithm.

Introduction This repository is for Deep Learning agent of Starcraft2. It is very similar to AlphaStar of DeepMind except size of network. I only test

Hierarchical Token Semantic Audio Transformer Introduction The Code Repository for "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound

Graph Convolution Simulator (GCS) Source code for "Understanding Knowledge Integration in Language Models with Graph Convolutions" Requirements: PyTor

Pruner for nested cross-validation - Sphinx-Doc Nested cross-validation is necessary to avoid biased model performance in embedded feature selection i

ES_OTN_Public Carlos Güemes Palau, Paul Almasan, Pere Barlet Ros, Albert Cabellos Aparicio Contact us: [email protected], contactus@bn

Object Detection using YOLO from PyImageSearch By applying object detection, you’ll not only be able to determine what is in an image, but also where

DNA sequence classification by Deep Neural Network: Project Overview worked on the DNA sequence classification problem where the input is the DNA sequ

RegNet Pytorch Implementation of "Desigining Network Design Spaces", Radosavovic et al. CVPR 2020. Paper | Official Implementation RegNet offer a very

YOLOv5-ROS YOLOv5 + ROS2 object detection package This program changes the input of detect.py (ultralytics/yolov5) to sensor_msgs/Image of ROS2. Requi

Python-AmongUsProblem Project in which we modelise an Among Us problem using graph theories. The rules are as following: Total of 100 players 10 playe

CAP-Classification-CRNN A deep learning model based on Inception modules paired with gated recurrent units (GRU) for the classification of CAP phases

TGraM Multi-Object Tracking in Satellite Videos with Graph-Based Multi-Task Modeling, Qibin He, Xian Sun, Zhiyuan Yan, Beibei Li, Kun Fu Abstract Rece

[AAAI2022] Detecting Human-Object Interactions with Object-Guided Cross-Modal Calibrated Semantics Overall pipeline of OCN. Paper Link: [arXiv] [AAAI

Official code for paper "ISNet: Costless and Implicit Image Segmentation for Deep Classifiers, with Application in COVID-19 Detection". LRPDenseNet.py

TailCalibX : Feature Generation for Long-tail Classification by Rahul Vigneswaran, Marc T. Law, Vineeth N. Balasubramanian, Makarand Tapaswi [arXiv] [

MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition Paper: MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition accepted fo

Source Code of AAAI22-2171 Introduction The source code includes training and inference procedures for the proposed method of the paper submitted to t

TDY-CNN for Text-Independent Speaker Verification Official implementation of Temporal Dynamic Convolutional Neural Network for Text-Independent Speake

APSIPA-SER-with-A-and-T This code is the implementation of Speech Emotion Recognition (SER) with acoustic and linguistic features. The network model i

Emotion-Detection Job Assignment System by Real-time Emotion Detection Emotion is the essential role of facial expression and it could provide a lot o

This is a python based command line Network Scanner utility, which input as an argument for the exact IP address or the relative IP Address range you wish to do the Network Scan for and returns all the available IP addresses with their MAC addresses on your current Network.

NeuralForecast is a Python library for time series forecasting with deep learning models. It includes benchmark datasets, data-loading utilities, evaluation functions, statistical tests, univariate model benchmarks and SOTA models implemented in PyTorch and PyTorchLightning.

Anonymously Reverse shell over Tor Network using Hidden Services without portfortwarding Tor ağı ile Dark Web servislerini kullanarak anonim biçimde p

Network tests automation Network tests automation About this repository Requirements Requirements on your laptop Requirements on the switches Quick te

Object tracking is one such application of computer vision where an object is detected in a video, otherwise interpreted as a set of frames, and the object’s trajectory is estimated. For instance, you have a video of a baseball match, and you want to track the ball’s location constantly throughout the video.

Recovering-Brain-Structure-Network-Using-Functional-Connectivity Framework: Papers: This repository provides a PyTorch implementation of the models ad

Detect and Classify Brain Tumor using CNN. A system performing detection and classification by using Deep Learning Algorithms using Convolution-Neural Network (CNN).

Earthquake detection via fiber optic cables using deep learning Author: Fantine Huot Getting started Update the submodules After cloning the repositor

Python command line tool and python engine to label table fields and fields in data files. It could help to find meaningful data in your tables and data files or to find Personal identifable information (PII).

Classification using Deep Learning Requirements PyTorch version = 1.9.1+cu111 Python version = 3.8.10 PyTorch-Lightning version = 1.4.9 Huggingface

Python project that aims to discover CDP neighbors and map their Layer-2 topology within a shareable medium like Visio or Draw.io.

MV_FaceDetectionWithSIFT Face recognition project by matching the features extracted using SIFT. By : Aria Radmehr Professor : Ali Amiri Dependencies

This project is a web porting for NVlabs' StyleGAN2, to facilitate exploring all kinds characteristic of StyleGAN networks. Thanks for NVlabs' excelle

AvatarGAN ✨ Generate Cartoon Images using DC-GAN Deep Convolutional GAN is a generative adversarial network architecture. It uses a couple of guidelin

pixel_character_generator Generating retro pixel game characters with Generative Adversarial Networks. Dataset "TinyHero" included. Dataset TinyHero D

🔥🔥🔥🔥 YOLO with Transformers and Instance Segmentation, with TensorRT acceleration! 🔥🔥🔥

The unified machine learning framework, enabling framework-agnostic functions, layers and libraries. Contents Overview In a Nutshell Where Next? Overv

R-YOLOv4 This is a PyTorch-based R-YOLOv4 implementation which combines YOLOv4 model and loss function from R3Det for arbitrary oriented object detect

Expense Tracker is a very good tool to keep track of your expenseditures and the total money you saved.

Image Segmentation and Object Detection in Pytorch Pytorch-Segmentation-Detection is a library for image segmentation and object detection with report

RuCLIPtiny Zero-shot image classification model for Russian language RuCLIP tiny (Russian Contrastive Language–Image Pretraining) is a neural network

YOLTv5 rapidly detects objects in arbitrarily large aerial or satellite images that far exceed the ~600×600 pixel size typically ingested by deep learning object detection frameworks.

Anomaly-detection-Feature-Selection Evaluate on three different ML model for feature selection using Breast cancer data. ML models: SVM, KNN and MLP.

README.md PrePareded anaconda env requirements.txt clova AI → deep text recognition → trained weights (ex, .pth) wpod-net weights (ex, .h5 , .json) ht

LabGraph is a a Python-first framework used to build sophisticated research systems with real-time streaming, graph API, and parallelism.

Credit Card Fraud Detection, used the credit card fraud dataset from Kaggle

Deep learning based model for Cyro ET Sub-tomogram-Detection High degree of stru

This is a model made out of Neural Network specifically a Convolutional Neural Network model. This was done with a pre-built dataset from the tensorflow and keras packages. There are other alternative libraries that can be used for this purpose, one of which is the PyTorch library.

This project is a convolutional neural network (CNN) that analyzes self-generated images in a variety of languages to find etymological similarities. Specifically, the goal is to prove that computer vision can be used to identify cognates known to exist, and perhaps lead linguists to evidence of unknown cognates.