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DroneImage-segmentation
This is a PyTorch-based project for drone image segmentation. The goal of this project is to segment objects and regions of interest within aerial images captured by drones. Image segmentation is a crucial task in computer vision and has various applications, including agriculture, urban planning, and environmental monitoring.Predictoo
Predictoo is a python package which allows to predict the future of a time series.Predictoo contain 10 deep learning model .It is a tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth. It is based on an additive model where non-linear trends are fit with yearly and weekly .DncnnV
This is a PyTorch implementation of DNCnn(modified) for image denoising and deblurring. Dncnn is a deep convolutional neural network for image denoising. It is a fully convolutional network with residual learning and batch normalization.my_portfolio
fuel-economy-data-analysis
OCR-ssl
Denoiser_Encoder-With-DNcnn
this project is created based on state of the art model Dncnn . This is a simple implementation of image denoisingVideo_Frame_Prediction
The Convolutional LSTM architectures bring together time series processing and computer vision by introducing a convolutional recurrent cell in a LSTM layer. In this example, we will explore the Convolutional LSTM model in an application to next-frame prediction, the process of predicting what video frames come next given a series of past frames.transformer-VIT-_object_detaction
In the past few years, there has been a rapid increase in the use of computer vision technology in many applications such as security, surveillance and machine learning. One of the applications that have seen significant growth in the past few years is object detection. Object detection is the process of detection process if detective objects suchImage-segmentation
Semantic segmentation is a type of computer vision technique that assigns a label to every pixel in an image. The label indicates the class of object that the pixel represents. Semantic segmentation is used in tasks such as self-driving cars, where it is important to know not only the boundaries of objects, but also what those objects are.news_classification
The main goal of this project is to make a simple news keyword classifier. The classifier will be trained on a dataset of news articles and their respective keywords. The classifier will then be able to classify a news article into one or more keywords.image_classification_pipeline
The main goal of this project is to create an image classification pipeline in Keras using several models and to walk you through all of the necessary steps in Keras to create a good and accurate model. This model can be utilized for both binary and multi-class classification. This project explains how to use Keras to train a model, including how to design different types of models, how to integrate transfer learning, how to prepare a data set for training, data augmentation, a data loader/data generetor, and how to visualize the results.how to handel and use build in callback fucntions, Compare the outcomes, learn how to use custom metric, how to reduce the traing time with keras mixed precision and more. In a simple word this pipeline contain all the importent aspet of keras for imagae clssificationflask-web-templates
project2
Diffusion__
IDC-Classification
AmzadHossainrafis
Amzad's portfolioAmzadHossainrafis.github.io
GAN_s
resume-classifier
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