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Development Technology

RF-DETR: How to Train for Object Detection on a Custom Dataset

Learn to train RF-DETR, the real-time, transformer-based object detection model, on your custom dataset! This step-by-step tutorial covers setup, training, and achieving SOTA accuracy—perfect for edge-ready, high-performance detection. code: https://github.com/pyresearch/RF-DETR-SOTA-Real-Time-Object-Detection-Model notebook: https://colab.research.google.com/github/pyresearch/notebooks/blob/main/notebook/how_to_finetune_rf_detr_on_detection_dataset.ipynb Level Up Your AI Skills with PyResearch! Unlock the potential of AI and Computer Vision with PyResearch’s cutting-edge tools, resources, and services: 🔹 […]

Development Technology

ADML S2E5 – Optimizing Supply Chain with Reinforcement Learning and Graph NNs

Abstract: Distribution networks are a crucial part of supply chains that often entail highly complex optimization problems. For example, optimizing the transportation cost of multiple kinds of goods over a time horizon with order consolidation requirements is an NP-hard problem. In this presentation, we will explore a distribution problem with such characteristics, called the Shipping […]

Development Technology

Unsupervised Object Detection with CutLER

In this stream we review the paper: “Text-To-4D Dynamic Scene Generation”. http://people.eecs.berkeley.edu/~xdwang/projects/CutLER/ https://arxiv.org/pdf/2301.11320.pdf Like 👍. Comment 💬. Subscribe 🟥. ⌨️ GitHub https://github.com/hu-po 📸 Instagram http://instagram.com/gnocchibengal Patreon: Coming Soon Bitcoin (BTC): Coming Soon Etherum (ETH): Coming Soon #machinelearning #ai #unsupervisedlearning #pytorch #meta source

Development Technology

AI Network Challenges & Solutions with Arista

Hugh Holbrook, Chief Development Officer at Arista, presented on the unique challenges and solutions associated with AI networking at AI Field Day 5. He began by highlighting the rapid growth of AI models and the increasing demands they place on network infrastructure. AI workloads, particularly those involving large-scale neural network training, require extensive computational resources […]