TMCnet

Bridging Silence: A Real-Time Sign Language to English Text Translation System Using Python, OpenCV, and Convolutional Neural Networks

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive ...

NITK uses machine learning to predict landslides in Western Ghats

NITK develops SVALSA, a machine learning-based landslide warning system for the Western Ghats, enhancing disaster ...
Live Science

Cold snap in Florida made Burmese python puke up a whole deer

Difficulty digesting large meals may limit where these temperature-sensitive snakes can call home — and that might be a good thing in places where they're invasive. When you purchase through links on ...
Assembly Mag

Traditional Machine Learning for Practical Machine Vision: It’s Been There All Along

Powerful and practical machine learning tools for machine vision applications are already available to everyone, even if you’re not a data scientist. It might come as a bit of a surprise, but machine ...
Frontiers

Machine-learning algorithm to predict home delivery after antenatal care visit among reproductive age women in East Africa

Background: Maternal and child health remains a global public health issue, particularly in low- and middle-income countries where maternal and child mortality are extremely high. The World Health ...
IEEE

K-Nearest Neighbor Algorithm Based on the Framework of Ordered Pair of Normalized Real Numbers

Abstract: The K-nearest neighbors (kNNs) algorithm, a cornerstone of supervised learning, relies on similarity measures constrained by real-number-based distance metrics. A critical limitation of ...
BMJ

Prediction of zero-dose children using supervised machine learning algorithm in Tanzania: evidence from the recent 2022 Tanzania Demographic and Health Survey

Objectives This study aimed to employ machine learning algorithms to predict the factors contributing to zero-dose children in Tanzania, using the most recent nationally representative data. Design ...
Frontiers

Interpretability Versus Accuracy: A Comparison of Machine Learning Models Built Using Different Algorithms, Performance Measures, and Features to Predict E. coli Levels in ...

Existing datasets collected in 2018 (Weller et al., 2020b) and 2017 (Weller et al., 2020c) were used as the training and testing data, respectively, in the analyses reported here. Although the present ...