Artificial Intelligence

Get the most out of your training, scoring, algorithms and frameworks on Intel® architecture for Deep Learning and Artificial Intelligence.

Detecting Acute Lymphoblastic Leukemia Lymphoblasts with Tensorflow/oneAPI/OpenVINO & Neural Compute Stick

URL: https://github.com/aiial/hias-all-oneapi-classifier

Description:

An open-source classifier programmed using the Intel® Distribution for Python* and trained using Intel® Optimization for TensorFlow*. The model is deployed on a Raspberry 4 using Intel® Distribution of OpenVINO™ Toolkit and inference is carried out using Neural Compute Stick 2.

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mRNA levels predictive model

URL: https://github.com/ofiryaish/NLA-project-20

Description:

The mRNA levels are essential for understanding cell behavior. A predictive model for mRNA levels, given the mRNA sequence and its initial level value, is presented. The predictive model is based on least-squares regression. Solving the problem with standard methods creates overfitting.

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NephronAI | Fighting chronic kidney disease using deep learning

URL: https://github.com/ayushanand18/nephron-ai

Description:

Around 37 million people worldwide die of chronic kidney disease each year. Still there are no extensive researches going on in the field. NephronAI helps us fight chronic kidney disease using deep learning. It is a web-based tool that can be used to detect as well as know the cause of the disease.

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Detecting Liveness of a Fingerprint using Deep Learning

URL: https://github.com/souvikbaruah/CNN-Model-Detecting-Liveness-of-Fingerprint-using-Deep-Learning-

Description:

A CNN model designed to distinguish between a fake fingerprint and a live fingerprint. This concept can be used on fingerprint scanners to prevent different kinds of fraud. A comparison in performance and accuracy has also been made by making use of the predefined VGG16 Architecture.

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