Abstract: In recent years, numerous designs have used systolic arrays to accelerate convolutional neural network (CNN) inference. In this work, we demonstrate that we can further speed up CNN ...

Eric Gutiérrez, 6th February 2026. A Python implementation of a 1-hidden layer neural network built entirely from first principles. This project avoids deep learning libraries (like TensorFlow or ...

Abstract: To address the degradation in radiation performance caused by external deformations in variable-curvature cylindrical conformal antenna arrays, this letter proposes a real-time beam pattern ...

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...

A project group including Tongji University, Stanford University and Shanghai Institute of Technical Physics has developed a camera said to help solve the inherent imaging trade-off between bandwidth ...

This video is an overall package to understand Dropout in Neural Network and then implement it in Python from scratch. Dropout in Neural Network is a regularization technique in Deep Learning to ...

ABSTRACT: With the advent of the 5G and future 6G, base stations will be used as station controllers. The antenna systems are networked and equipped with a processor to optimize the detection of ...

The earthquake simulation shaking table array is an important experimental equipment with a wide range of applications in the field of earthquake engineering. To efficiently address the complex ...

Accurate brain tumour segmentation is critical for diagnosis and treatment planning, yet challenging due to tumour complexity. Manual segmentation is time-consuming and variable, necessitating ...

Non-invasive brain-computer interfaces (BCI) hold great promise in the field of neurorehabilitation. They are easy to use and do not require surgery, particularly in the area of motor imagery ...