Blind Object Classification
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Updated
Dec 18, 2018 - C++
Blind Object Classification
Vehicle Detection application based on OpenCV, YOLOv3 and PyQt5 GUI - implementation in terms of Software Engineering course on AGH University of Science and Technology
A simple web site to classify flowers into 5 classes using CNN
A simple object classificator
PyTorch code for MemSAC. To appear in ECCV 2022.
Implemented a CNN to classify images from CIFAR-10 dataset
Unsupervised Learning Classification with K-Means
Here is a Deep Learning solution for handwritten digits recognition topic, inspired by three references mentioned in the main notebook.
Easily train your semantic segmentation, part segmentation or object classification task with different pointcloud networks. In development.
A real-time project that detects and classifies urine cells from microscopic images. This project provides information on urinary health and diseases and assists doctors.
Computer vision object classifier for Android
Machine learning tool that provide features such as object detection, object classification, image segmentation, and image classification. Tech Stack-Machine learning, Django, Python.
Computer vision based coin counter using DL
This is an AI system that aims to make AI object classification accessable to anyone, and expand the reach of classical AI image classification, this set also includes pre-trained models. NOT CREATED BY A MEDICAL PROFESSIONAL, USE AT YOUR OWN RISK.
Implement a safe autonomous navigation in a simulated 3D environment. In the simulation there will be traffic lights, that must be recognized by the self-driving car using a camera. Based on the state of the traffic light the car keeps moving, reduce the velocity, or stops. The self-driving car needs to be able to not exceed the maximum velocity…
Simple classification script that uses VGG16. Learned on image-net
Computes loss between two sets of entities using the optimal assignment based on the Hungarian algorithm.
Aggregates labeled vehicle images and classifies vehicle images on granularity of make, model, and generation
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