Abstract: Due to the strong feature extraction capabilities, convolutional neural networks (CNNs) have been utilized for various tasks, including image recognition, object detection, and natural ...

To address this challenge, we propose a Rebuild Convolution Block Attention Module-based Convolutional Neural Network (RCBAM-CNN) designed to accurately classify lung nodules from CT scans. The ...

The CNN Accelerator IP is paired with the Lattice Neural Network Complier Tool. The compiler takes the networks developed in Caffe or TensorFlow, analyzes for resource usage, simulates for performance ...

A deep learning-based system that detects facial expressions from webcam input and classifies them into seven emotions — Angry, Disgust, Fear, Happy, Neutral, Sad, and Surprise — using a CNN model and ...

The IBS-Yonsei research team introduces a novel Lp-Convolution method at ICLR 2025. A team of researchers from the (IBS), ...

In computer vision, convolutional networks (CNNs) often adopts pooling to enlarge receptive field which has the advantage of low computational complexity. However, pooling can cause information loss ...

The core innovation lies in replacing the traditional DETR backbone with ConvNeXt, a convolutional neural network inspired by ...

Welcome to Learn with Jay – your go-to channel for mastering new skills and boosting your knowledge! Whether it’s personal development, professional growth, or practical tips, Jay’s got you covered.

Based on the deep learning method, the convolutional neural network model is used to extract the newly produced ... Reference [9] proposes a NILM-based energy management system for appliance-level ...