This repository is a part of the project for the course Computer Vision at the University of Zaragoza. The goal of the project is to classify landmarks using Neural Networks.
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Updated
May 16, 2023 - Jupyter Notebook
This repository is a part of the project for the course Computer Vision at the University of Zaragoza. The goal of the project is to classify landmarks using Neural Networks.
Automated Web-based Malaria Detection System Using Machine Learning, Deep Learning and Transfer Learning Techniques: A Comparative Analaysis
Universal Image classifier
As part of a Cloud and Distributed Systems lecture, we developed a scalable application in the form of an image classifier meant for deployment on Kubernetes. We also created our own Kubernetes infrastructure bare metal server, complete with loadbalancing and ingress-support.
This notebook is my attempt at predicting ages of children from the X-Ray images of their hands.
Workshop CDK Template to provision infra for the Deep Visual Search workshop
Udacity Machine Learning Engineer Nanodegree Convolutional Neural Networks (CNN) Project: Dog Breed Classifier
Recyclables manager fine-tuned on XCeption using Kaggle's GPU instances.
🐠 Recognition of 20 Mediterranean fish species using different state-of-the-art CNNs architectures, transfer learning and data augmentation.
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
[Bachelor Graduation Project] Use Xception model for face anti-spoofing
Transfer learning with Xception CNN to recognize kids' toys and gear
CNN Binary Classification Model.
Plataforma para clasificar motos Calle, Chopper, Cross, Cuatriciclos, Deportivas, Enduro, Naked, Scooters y Touring) usando Xception.
Adopted a convolutional neural network for COVID-19 testing. Examined the performance of different pre-trained models on CT testing and identified that larger, out-of-field datasets boost the testing power of the models.
위조 영상 식별을 위한 Xception 모델의 일반화 성능 분석
Signature Classification on ICDAR 2011 Signature Dataset
Chainer implementation of the paper "Xception: Deep Learning with Depthwise Separable Convolutions" (https://arxiv.org/abs/1610.02357).
Identify dog or cat with deep learning
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