🧐7 things you should know about the Focal Loss:
📌 It was introduced in the RetinaNet paper to address the foreground-background class imbalance encountered during training of dense detectors (one-stage detectors)
...
Check out this great event #DataScience community. Nov 10: Meet the data scientist who's working on Amazon's Alexa: https://t.co/rbBxF4YzH1 #OpenData#DataViz
🥇YOLOX beat YOLOv5. They won the 1st Place on Streaming Perception Challenge (Workshop on Autonomous Driving at CVPR 2021).
I briefly explain how they created it, here below👇
YOLOX will be soon supported in our IceVision Framework (Repo: https://t.co/wNQen4X65M)
#SmallObjectDetection
Here is another good technique to detect small objects when you have access to high resolution images. Inference is done on patches/slices and then stitched together.
Repo: https://t.co/FsMPHZzUFP
AI is cool. Not just because it can recognize our face or recommend a movie that we actually like. But because it can help satisfy one of our basic human needs: Food. https://t.co/PyjJ3K2TOB @ai_fast_track@SharpestMindsAI@fastdotai#DeepLearning
This paper by Rieke et al shows Federated Learning as one of the possible ways of bridging silos in medical data without compromising confidentiality. https://t.co/0u2Pd7BnTi #MachineLearning#DataScience#deeplearning#medicaldata
#SmallObjectDetection
Interesting approach for detecting tiny objects as small as 2 × 2 pixels. It uses Multi-Scale Semantic Segmentation. Anchor free.
Paper: Oriented Bounding Boxes for Small and Freely
Rotated Objects
pdf: https://t.co/H7H3cMKZm3
abs: https://t.co/Pu8s9TTo67