At a Glance · AI-generated

A three-part educational series on computer vision object detection techniques launched in late October 2017, beginning with foundational methods including Gradient Vector, Histogram of Oriented Gradients, and Selective Search. The series expanded in mid-December to cover convolutional neural networks, deformable parts models, and the OverFeat architecture. The final installment, published December 30, focused on the R-CNN family of detection algorithms, completing a comprehensive overview of both classical and deep learning approaches to object detection.