As a team, we've witnessed the alarming failure rates of enterprise AI products, with estimates ranging from 70% to 80%. These failures are expected to persist, with only 15% of AI use cases projected to succeed by 2022. The challenges…
Human Activity Recognition (HAR) is a cutting-edge field within computational science and engineering that focuses on identifying and categorizing human actions based on sensor data. HAR systems have wide-ranging applications in areas such as wellness, healthcare, security, and sports performance.…
Pattern recognition, a fundamental aspect of machine learning, holds immense significance across various industries and applications. By analyzing data and identifying patterns, this cognitive process enables classification, clustering, and abstraction. With advancements, pattern recognition can now recognize obscured patterns and…
In this article, we'll explore the concept of Intersection over Union (IoU) and its significance in object detection. IoU is a widely used metric to evaluate localization accuracy in computer vision. By measuring the overlap between predicted and ground truth…
Mean Average Precision (mAP) is a crucial metric for evaluating object detection models, measuring their performance and accuracy. By calculating the mean of average precision values, mAP provides a comprehensive assessment of a model's capability. It incorporates sub-metrics such as…
This article delves into the YOLO (You Only Look Once) algorithm, a highly efficient object detection method widely used in fields such as surveillance, self-driving cars, and robotics. By utilizing a fully convolutional neural network, YOLO enables real-time object detection,…
