Submission - Last Project : Image Classification - Machine Learning for Beginners - Machine Learning Path - DICODING

Deep learning network to visually recognize traffic signs, trained on the German Traffic Sign Benchmark (GTSB).

Academic Machine Learning (6 months) Sessional Project

Pistachios are nutritious nuts that are sorted based on the shape of their shell into two categories: Open mouth and Closed mouth. The open-mouth pistachios are higher in price, value, and demand than the closed-mouth pistachios. Because of these differences, it is considerable for production companies to precisely count the number of each kind.

This project is about how to apply image data augmentation in Keras. And focused on using the ImageDataGenerator class from Keras’ image preprocessing package, and gives insight of a variety of options available in this class for data augmentation and data normalization.

The aim of this project is to implement an image classifier based on convolu- tional neural networks. Starting by implementing a simple shallow network and then refining it until a pre-trained ResNet18 is implemented, showing at each step how the accuracy of the model improves. The provided dataset (from [Lazebnik et al., 2006]) contains 15 cate…

Team Project for Data Analysis With Deep Learning class

Image Classification using Convolutional Neural Networks (CNN)!

Example application for training Google's pretrained Vision Transformer model on an image classification task with a large number of labels

👤 Detect age and gender from facial images using deep learning with CNNs like VGG16 and ResNet, achieving high accuracy under various conditions.

Predefined pipelines for image augmentation

implementation of two deep learning models—UNet and a custom-built CANet—for semantic segmentation of Indian traffic scenes. Using the India Driving Dataset, the goal is to accurately segment various traffic elements to facilitate applications in autonomous driving and smart traffic management.

Tumor detection using deep learning(Keras)

The project aimed to push image captioning technology forward by combining recent advances in image recognition and language modeling to generate novel, descriptive captions that go beyond just naming objects and actions

Face verification determines whether two images represent the same person

A lightweight, high-performance toolkit for generating robust image datasets. Features a Streamlit-based UI for real-time augmentation previews and batch processing, specifically optimized for document scanning, OCR, and computer vision workflows.

Convolutional Neural Network (CNN) with image augmentation project to classify hand image of rock, paper, and scissors

A CNN model for accurate identification of diseases in potato, tomato, and pepper plants.

Projekat za kurs: Naučno izračunavanje