TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you''ve ever built a predictive model, worked on a ...
IEEE

TensorFlow and Pytorch Model Deployment on Edge Devices

Abstract: This paper presents the design of a framework for loading a pre-trained model in PyTorch on embedded devices to run local inference. Currently, TensorFlow Lite is the most widely used ...
GitHub

RTX 5090/5060 Docker: PyTorch & TensorFlow for NVIDIA Blackwell GPUs

The first Linux Docker container fully tested and optimized for NVIDIA RTX 5090 and RTX 5060 Blackwell GPUs, providing native support for both PyTorch and TensorFlow with CUDA 12.8. Run machine ...
GitHub

This repository intends to provide a comprehensive guide to deploy RT-DETR with TensorRT, based on both Python and C++.

It is worth noting that this repository is learning-oriented, and is not intended for production use. Pytorch Model fp32 48.1 Onnx fp32 48.1 trt engine fp32 48.1 trt engine fp16 48.0 Onnx Default mtq ...
IEEE

Python Overheads Using Ackermann Function Benchmark: Performance and Power Consumption

Abstract: The main focus of this manuscript is on the impact of running Python codes in two different environments. Firstly, the Python Integrated Development and Learning Environment (IDLE), and ...