Obtaining meaningful results from the data set using the model trained with machine learning methods.

Detection and localization of Asian hornets with a CNN using PyTorch

#AI Tensorflow, Machine Learning and Building a data model to recognize object detection with Keras back-end. This a research work. This library is designed for everyone to learn fast.

This repository contains my practice of Introduction to Computer Vision and Image Processing lab notebooks.

For MLSA Workshop

implementation of using model.h5 on flask

Classificationbox Toolkit - a .Net wrapper for Machine Box's Classificationbox service and a CLI program using it to train a model and sort image folders

Image classification for dogs and cats with VGG-16 using PyTorch. Model accuracy: 99.6%. Classification API included

this project includes the model to predict the number of requests for bike rental according to the dataset.

Moving train on railway line with CSS3

Uilizing Tensorflow and openCV frameworks, we have created a Face Mask Detection Software Script.

Two-stream cnn models for action recognition on the UCF-101 dataset

in this project, a model is presented to identify and recognize customers who will leave the cycle of existing customers.

Keras pretrained models (VGG16, InceptionV3, Resnet50, Resnet152) + Transfer Learning for predicting classes in the Oxford 102 flower dataset

YOLOv8 for Object Detection. This model is trained for the custom data set. YOLOv8 is an Open Source SOTA model built and maintained by the Ultralytics team. You guys can use this model for your custom dataset. I tried to provide the model just like plug and play.

Classify UCF101 videos using one frame at a time with a CNN(InceptionV3)

Social Emotion Analysis | SEA

This uses machine learning to recognize faces to mark attendance.