An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy ...

Abstract: This paper presents an efficient reconfigurable parameterized convolutional neural network (CNN) accelerator designed for FPGA platforms. The core of the accelerator allows flexible ...

A high-performance AI framework enhances anomaly detection in industrial systems using optimized Graph Deviation Networks and graph attention ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Raman spectroscopy in biological applications faces challenges due to complex spectra, ...

Scientists have created a novel probabilistic model for 5-minutes ahead PV power forecasting. The method combines a convolutional neural network with bidirectional long short-term memory, attention ...

You can create a release to package software, along with release notes and links to binary files, for other people to use. Learn more about releases in our docs.

Abstract: This paper presents a lightweight Convolutional Neural Network (CNN) model for face recognition. The network structure has three convolutional layers, three pooling layers, one flattening ...

Skin conditions are a worldwide health issue that requires prompt and accurate diagnosis in order to be effectively treated. This study presents a Convolutional Neural Network (CNN)-based automated ...

Background: Early detection is clinically crucial for the strategic handling of sarcopenia, yet the screening process, which includes assessments of muscle mass, strength, and function, remains ...