Instead of recognizing the motion, this study examines the possibility of identifying the transition between gaits to achieve in-time detection. This study used the data from IMU sensors for future mobile applications. Furthermore, we tested using two machine learning networks: a linearfFeedforward...
or using interpolated results for smooth video processing by separating detection and drawing loops: const human = new Human(); // create instance of Human const inputVideo = document.getElementById('video-id'); const outputCanvas = document.getElementById('canvas-id'); let result; async func...
While active efforts are advancing medical artificial intelligence (AI) model development and clinical translation, safety issues of the AI models emerge, but little research has been done. We perform a study to investigate the behaviors of an AI diagnos
Machine Learning in Forensic Genetics Leveraging Molecular Markers for Body Fluid Identification in Complex Mixtures The Integration of Microhaplotypes in Forensic DNA Analysis From DNA Mixtures to Accurate Phenotype Predictions: Barcoding Single Cells with PhenoTrivium+ Assay Enhancing Human DNA Detection and...
These two models were fused to create a multi-saliency map, and both characteristics were used simultaneously to improve detection rates. To handle problems such as asymmetry, a rotation matrix was calculated around the center, and Histogram of Oriented Gradient (HOG) features descriptor were ...
Human detection and Tracking Introduction In this project we have worked on the problem of human detection,face detection, face recognition and tracking an individual. Our project is capable of detecting a human and its face in a given video and storing Local Binary Pattern Histogram (LBPH) featu...
We could also achieve more than 94% accuracy in classifying the direction, speed and distance and idengifying subjects using the reduced feature set extracted from two pairs of PIR sensors of each of the three modules. 展开 关键词: pyroelectric infrared sensor human movement detection human id...
Human learners can generalize a new concept from a small number of samples. In contrast, conventional machine learning methods require large amounts of data to address the same types of problems. Humans have cognitive biases that promote fast learning. H
A comparative study on various Machine Learning Techniques for Human Activity Recognition and Fall Detection To bridge the gap in the mobile technologies, this paper is an extensive survey of fall detection using machine learning algorithms. Initially, we present... N Sao,D Dubey 被引量: 0发表:...
The machine learning model developed can be used for accurate papillae detection and positioning on segments from a single person’s tongue. Figure6shows the method accurately positions the fungiform form (in blue) and filiform (in yellow) on a tongue segment from one participant. This automated...