The project involves using brain-machine computing to predict emotions. This likely involves using brainwave data to identify patterns that correspond with different emotional states.
The project is currently in progress, i am still collecting data, developing algorithms........
Air wiggle ; Project submission on https://devmesh.intel.com/
for the Learned worth consult digital technology company incoporated in Nigeria, cac no ; BN 3701056
https://www.github.com/free2ride19/air-wiggler
https://www.github.com/caseg-network/air-wiggler
Air wiggle aims to be a project
Weeds are unwanted trespassers in the agricultural business. Let’s leverage computer vision and deep learning to detect the presence of weeds in crops. This will enable targeted remediation techniques to remove them from fields with minimal environmental impact.
a user-friendly interface to perform single-cell RNA sequencing analysis on selected datasets using various machine learning classification algorithms. The objective of the project is to help researchers, biologists, and clinicians to identify and classify cancerous and non-cancerous cells accuratel
The project is based on one of the themes Intel® oneAPI Hackathon for Open Innovation. It aims to devise a Machine Learning tool to predict the quality of freshwater
Derma diseases are common conditions with a variety of causes. Some of them can cause death like Melanoma, but with early diagnosis, we can save many lives.
Dermato.AI is an AI tool that can identify, detect, and segment of 3 types of similar-looking skin diseases.
This project aims to predict freshwater quality using machine learning techniques, specifically Adaptive Particle Swarm Optimization (APSO) and Convolutional Neural Network (CNN). The APSO algorithm is used for feature selection, while the CNN is used for classification. The model achieved an accura
The proposed method uses a Residual Network (ResNet) architecture with Auto Mixed Precision (AMP) to classify images of crops and weeds. The use of AMP allows for dynamic adjustment of the precision of computations during training and inference, which can improve the model's performance.
Modern technologies allow for noninvasive medical aid. Stroke is the most fatal of the four major cardiovascular conditions, yet early detection can save a patient's life. Using machine learning techniques, this project implements a clean method for the early identification of strokes with the help
基于OneAPI技术的并行随机森林实现,旨在提高随机森林算法的性能
Parallel random forest implementation based on OneAPI technology, aiming to improve the performance of random forest algorithm
Individual initiative in Brazil of the world's first Linux image with native kernel 6.2-rc5 or higher with Intel ARC stable open source driver. All GPU detection procedure takes place automatically during installation.
We will create a simple Neural Network using CUDA and DPC++. Then, we will use oneAPI to test our code using an Intel base workstation and compare it with the performance of an NVIDIA GPU.
Using EVs' charging data, I explored when drivers are likely to plug in their cars, and how much additional electricity demand will be created when the number of EVs increases.