this post was submitted on 12 Jan 2024
4 points (100.0% liked)

Open Course Lectures

575 readers
3 users here now

This is a place to post freely available full-length lectures and courses of the sort available through MIT OCW. These are primarily intended for self-study and professional development.

Looking for something?

Search this community 🔍

Try searching for hashtags representing the subject (e.g. #math).

Rules:


Related Communities

!autodidact@slrpnk.net

founded 1 year ago
MODERATORS
 

Institution: Stanford
Lecturer: Fei-Fei Li, Justin Johnson, Serena Yeund
University Course Code: CS 231
Subject: #computervision #machinelearning


Description: Computer Vision has become ubiquitous in our society, with applications in search, image understanding, apps, mapping, medicine, drones, and self-driving cars. Core to many of these applications are visual recognition tasks such as image classification, localization and detection. Recent developments in neural network (aka “deep learning”) approaches have greatly advanced the performance of these state-of-the-art visual recognition systems. This lecture collection is a deep dive into details of the deep learning architectures with a focus on learning end-to-end models for these tasks, particularly image classification. From this lecture collection, students will learn to implement, train and debug their own neural networks and gain a detailed understanding of cutting-edge research in computer vision.

no comments (yet)
sorted by: hot top controversial new old
there doesn't seem to be anything here