Retrieving product information from real-world image using GAN improved by residual networks.
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Updated
Jan 11, 2019 - Jupyter Notebook
Retrieving product information from real-world image using GAN improved by residual networks.
Source code of my "Object classification with artificial neural networks: A comparative analysis" paper and used scripts.
Segmentation of brain tumors from MRI images using ResNet and ResUNet, the idea of implementing residual blocks and reducing gradient fading.
Uses pediatric x-rays and data to build a classification model that can predict whether or not a patient has pneumonia.
Pokemon Classification Contest
Residual Neural Network Object Detector written for Pycocotool's library. Model implements custom skip block connections and uses a custom dataset loader for image classification object detection.
NLP methods is practiced including GPT, Machine-translation, Q&A models
Deep learning model to predict the normal flow between two consecutive frames, being the normal flow the projection of the optical flow on the gradient directions.
Robo-Chess, a comprehensive repository dedicated to developing chess engines using a variety of Deep Reinforcement Learning techniques
This is a model for detecting the crop disease detection using ResNet50. The dataset images are annoted in Roboflow and called in the program through it's api.
Программы по дисциплине "Современные методы глубокого машинного обучения" 6 семестра ФИТ НГУ
This repository contains the code and report for the final evaluation of the Deep Learning Applications module. It includes three exercises on Convolutional Neural Networks (CNNs), Reinforcement Learning, and Adversarial Training. Each exercise is designed to showcase different aspects of deep learning techniques and their applications.
Keras Functional API implementation of the 50-layer residual neural network (ResNet-50) and its application to sign language digit recognition
ChurnNet: Deep Learning Enhanced Customer Churn Prediction in Telecommunication Industry
Fraud detection via residual neural network. (+ DVC)
Residual learning: A new paradigm to improve deep learning-based segmentation of the left ventricle in magnetic resonance imaging cardiac images
Detection of 15 Key Facial Points Using Residual Neural Networks.
Code repository of my academic projects and case studies in Machine Learning during my Master's Degree program.
Code and data for our research work on "Comparative assessment of image super-resolution techniques for spatial downscaling of IMD Gridded Rainfall Data"
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