Object classification with basic computer vision techniques.
Final assignment for the computer vision course I took at university. The task was to classify objects in a picture using any tools we learned during the course. I used histogram equalization, Otsu thresholding, image dilation and other morphological operators for preprocessing and OpenCV's connected component labelling function for classifying objects according to their Hu moments.
Hso-groupie - A pwnable challenge in Real World CTF 4th
napari-yolov5 Plugin adapted from Ultralytics to bring YOLOv5 into Napari. Training and detection can be done using the GUI. Training dataset must be
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Status: Maintenance (expect bug fixes and minor updates) Welcome to Spinning Up in Deep RL! This is an educational resource produced by OpenAI that ma
CoGAIL Table of Content Overview Installation Dataset Training Evaluation Trained Checkpoints Acknowledgement Citations License Overview This reposito
PV-RAFT This repository contains the PyTorch implementation for paper "PV-RAFT: Point-Voxel Correlation Fields for Scene Flow Estimation of Point Clou
Transformers have accelerated the development of new techniques and models for natural language processing (NLP) tasks.
Nyström Attention Implementation of Nyström Self-attention, from the paper Nyströmformer. Yannic Kilcher video Install $ pip install nystrom-attention
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Learning Auto-Punctuation by Reading Engadget Articles Link to Other of my work 🌟 Deep Learning Notes: A collection of my notes going from basic mult
curriculum 8-week curriculum for AI Builders สารบัญ บทที่ 1 - Machine Learning คืออะไร บทที่ 2 - ชุดข้อมูลมหัศจรรย์และถิ่นที่อยู่ บทที่ 3 - Stochastic
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The Most Important Thing. Our code is developed based on: LXMERT: Learning Cross-Modality Encoder Representations from Transformers
Open-set Label Noise Can Improve Robustness Against Inherent Label Noise NeurIPS 2021: This repository is the official implementation of ODNL. Require
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time-series-classification Short and long time series classification via convolutional neural networks In this project, we present a novel framework f
SplineConv implementation for Paddle This module implements the SplineConv operators from Matthias Fey, Jan Eric Lenssen, Frank Weichert, Heinrich Mül
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