Image Processing & Computer Vision Video Series

Hallo teman-teman semuanya! 

Di post ini, saya akan membagikan video series yang akan membahas materi image processing dan computer vision. Video series ini akan membahas detail teorinya, kemudian di sesi berikutnya diikuti dengan praktek implementasi di pemrograman C++ menggunakan libary OpenCV.

Materi diadopsi dari bukunya Gonzales “Digital Image Processing” dari Chapter 1 hingga Chapter 12, yaitu Object Detection, ditambah dengan beberapa topik computer vision, seperti stereo vision. Adapun slide dan code-nya tersedia di link Github di sini. Slide dan code tersebut dapat digunakan secara gratis, baik untuk referensi perkuliahan hingga untuk self-study, dengan tetap mencantumkan sumbernya.

Semoga video series ini membantu teman-teman dalam memahami image processing dan computer vision, dan ikut membantu tumbuhnya iklim science & engineering di Indonesia. Salam 🙂

Understanding How Mask RCNN Works for Semactic Segmentation

Mask RCNN is extension of Faster RCNN. In 2017, this is the state-of-the-art method for object detection, semantic segmentation and human pose estimation. This awesome research is done by Facebook AI Research.  This post provides video series talking about how Mask RCNN works, in paper review style. May it helps.

1. Introduction to MNC, FCIS ad Mask RCNN for Instance Aware Semantic Segmentation

Understanding Faster R-CNN for Object Detection

Faster R-CNN is important research in object detection. It inspires many other methods how we can do object detection using deep learning, such as YOLO, SSD (Single Shot Detector) and so on. This post provides video series of how Faster RCNN works. The video series is made in paper review style. Hope it helps 🙂

1. Introduction to Faster R-CNN