New tutorial!🚀
— Adrian Rosebrock (@PyImageSearch) September 21, 2020
Intro to Automatic License/Number Plate Recognition with #OpenCV, #Python, and #DeepLearning 🚗🚚
- Detect license plates with OpenCV
- Extract characters
- #OCR license platehttps://t.co/SJyeME7sfV 👍#MachineLearning #ArtificialInteligence #AI #DataScience pic.twitter.com/UQk4Oq7m4V
The source code and checkpoints for BYOL are now available along with an updated version of the BYOL paper - including new theoretical and experimental insights.
— DeepMind (@DeepMind) September 15, 2020
Code: https://t.co/6QEUjmAt9L
Paper: https://t.co/qyaSXnPQjN https://t.co/8226fwJBuP
RAFT: Recurrent All Pairs Field Transforms for Optical Flow https://t.co/l7dfHUycS4 ECCV 2020 best paper award, fun reading. Like the careful use of inductive biases in the architecture design, other small details (e.g. convex combo upsampling). Shocked to see no Transformers :p pic.twitter.com/ubInOPe8cH
— Andrej Karpathy (@karpathy) September 6, 2020
Super excited to share our work on video completion at #ECCV2020!🤩Our method seamlessly removes objects, watermarks, or expands field-of-view from casually captured videos.
— Jia-Bin Huang (@jbhuang0604) September 4, 2020
Paper: https://t.co/JwT9bYN85V
Project: https://t.co/7raLq7jVQx
With @gaochen315, Ayush, and @JPKopf pic.twitter.com/eLGjINlbMC
Aditya Oke wrote a beginner tutorial on how to create a simple image search engine using PyTorch. The blog post walks through using auto-encoder, managing the dataset, training and saving the feature representations, and more with actual code samples. https://t.co/fUUhCcPDhw
— PyTorch (@PyTorch) September 2, 2020
Announcing C2D2, a #MachineLearning-based approach to improving colonoscopy screening coverage that performs real-time local 3D reconstruction of the colon during the procedure, and identifies regions outside the field of view of the endoscope. Read more ↓https://t.co/U3nonNBkxt
— Google AI (@GoogleAI) August 28, 2020
Axial-DeepLab is a novel network for image segmentation that enables long-range attention by replacing all convolution layers with sequential 1D height and width self-attention modules, resulting in state-of-the-art performance. Learn more below: https://t.co/N1h9U319Wy
— Google AI (@GoogleAI) August 26, 2020
New tutorial!🚀
— Adrian Rosebrock (@PyImageSearch) August 24, 2020
OCR Handwriting Recognition with #OpenCV, #Keras, and #TensorFlow 2
- Full tutorial w/ #Python code
- Learn how to OCR handwriting
- Includes pre-trained modelhttps://t.co/8IILGyrupA 👍#DeepLearning #MachineLearning #ArtificialInteligence #AI #DataScience pic.twitter.com/gSRAwr3NRB
In an effort to better understand how view selection affects #ContrastiveLearning models, we analyze the impact of viewpoint mutual information on downstream task performance. Learn more and grab the supporting code with pre-trained models at: https://t.co/6mEwWqT9pb pic.twitter.com/YCPGg8UhuP
— Google AI (@GoogleAI) August 21, 2020
Motion Capture from Internet Videos
— AK (@ak92501) August 19, 2020
pdf: https://t.co/yWbUJBqxeg
abs: https://t.co/EOrzAcKb2z
project page: https://t.co/cdEO4h7kVt pic.twitter.com/ulsCTugR2p
Deepfake detection challenge from R - RStudio AI
— RStudio (@rstudio) August 18, 2020
A couple of months ago, Amazon, FB, Microsoft, & other contributors initiated a challenge consisting of telling apart real and AI-generated (“fake”) vids. We show how to approach this challenge from #RStatshttps://t.co/1jAps9iDjD
Check out the 3 courses on Tabular Data, NLP and Computer Vision from the awesome Amazon MLU team https://t.co/5RwvtRnyb4 - kudos to Bree, Rachel, Brent and the rest of the crew. Built on https://t.co/fuWTPxe9I1.
— Alex Smola (@smolix) August 18, 2020
