Praxis: The First AI-Powered Autonomous Red Team Agent Goes Live

An AI terminal that thinks, adapts, and executes — turning natural language objectives into complete penetration test ...
搜狐

真心建议射频天线领域硕博士学透此文！科研就业双重丰收！

课程特别引入大语言模型（LLM）辅助科研新范式，从Ollama本地部署到LangChain射频智能体开发，帮助学员掌握AI Agent构建方法，推动射频信号智能处理技术向自动化、精准化、自适应方向发展。 核心目标：系统学习射频数据集的构建方法，掌握CNN、LSTM、Transformer ...
GitHub

Faster R-CNN with model pretrained on Visual Genome

Download the pretrained model and put it to the folder $load_dir. Run generate_tsv.py to extract features of image regions. The output file format will be a tsv ...
GitHub

A Python library to easily build, train, and test your CNN AI models.

This is a Convolutional Neural Network (CNN) library project implemented entirely from scratch using only low-level libraries like NumPy, PIL, SciPy and Cython no deep learning frameworks (e.g., ...
IEEE

Evaluating HLS4ML For Converting a CNN Model Into High Level Synthesis

Abstract: Deep learning models, although high-performing, often require hardware acceleration to be effectively deployed on Field Programmable Gate Arrays (FPGAs). This paper investigates the use of ...
IEEE

Python to FPGA: Automatic Implementation of custom CNN Model on FPGA

Abstract: With the rapid development of artificial intelligence neural network technology, the architecture of convolutional neural networks (CNNs) has been evolving towards greater complexity and ...
Scientific Research Publishing

Detection of Water Meter Digits Based on Improved Faster R-CNN ()

In order to more accurately detect the accuracy of word-wheel water meter digits, 2000 water meter pictures were produced, and an improved Faster-RCNN algorithm for detecting water meter digits was ...
Frontiers

Deep learning for skillful long-lead ENSO forecasts

El Niño-Southern Oscillation (ENSO) is one of the fundamental drivers of the Earth's climate variability. Thus, its skillful prediction at least a few months to years ahead is of utmost importance to ...
Frontiers

OpSeF: Open Source Python Framework for Collaborative Instance Segmentation of Bioimages

Various pre-trained deep learning models for the segmentation of bioimages have been made available as developer-to-end-user solutions. They are optimized for ease of use and usually require neither ...