Classify the severity stages of Diabetic Retinopathy
In this repository you can find the jupyter notebooks used to take part at the competitions created for the Artifical Neural Networks and Deep Learning exam at Politecnico di Milano.
Deep Learning models for Object Detection
Image Caption Generation using Keras' Pre-Trained Image Feature Extraction models and LSTM
A set of notebooks that leverage classical ML algorithms and DL neural nets using TF, Keras and Theano to address a series of issues in the field of conservation and biology.
Gathering and labeling data for an image-text fusion model for flavor classification of food based on recipes. Generating images using stable diffusion models, and using deep classification models like BERT, BiLSTM, and InceptionResnet.
Explore my comprehensive collection of AI models for blood cancer detection. Leveraging deep learning and medical imaging, these models aim to revolutionize early diagnosis and treatment, making a significant impact on the battle against blood cancers. #AI #HealthcareInnovation
This repository contains the jupyter notebooks used to take part at the competitions created for the Artifical Neural Networks and Deep Learning exam at Politecnico di Milano.
A Deep learning project for food classification on the popular Food-101 dataset using pre-trained CNNs like the Inception network, ResNets, and Inception-ResNets.
Malaria is one of the disease causing deaths worldwide. Detection of malaria is a physical task invloving pathologist to diagnosis the presence of parasite inside the microscopic view of thin blood smears. This process is prone to errors as it requires an experienced person. Also, eye sight plays a vital role in order to detect the malaria. Ther…
Address the crowd counting problem on the Mall dataset (sparse) by exploring regression-based (Xception) and density-based (CSRNet) approaches.
fine-tuning an image classification problem with transfer learning, using inResNetV2
KeepCoding Bootcamp Big Data & Machine Learning - Práctica Deep Learning
Image classification over a very small non-uniform dataset.
exploring image captioning
Coloring black and white images using autoecoders and transfer learning
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