An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy ...
Abstract: Electroencephalography (EEG) is an effective assessment tool to identify autism spectrum disorders with low cost, and deep learning has been applied in EEG analysis for extracting meaningful ...
Abstract: In this letter, we introduce the first spiking-based network optimized for synthetic aperture radar (SAR) ship detection and compare its performance with conventional neural networks (CNNs).
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This is a general purpose aimbot, which uses a neural network for enemy/target detection. The aimbot doesn't read/write memory from/to the target process. It is essentially a "pixel bot", designed ...
The geological structure of buried hill reservoirs is highly complex. This study aims to develop a new reservoir fluid identification method for buried hill reservoirs by integrating nuclear magnetic ...
This project contains implementations of simple neural network models, including training scripts for PyTorch and Lightning frameworks. The goal is to provide a modular, easy-to-understand codebase ...