Quantum gravity research links continuous parameters to local operators within the theory itself

A researcher at Kyushu University and his collaborators have shown that continuous parameters in quantum gravity may not be ...

AI Learned the Rules of the Universe and That Became a Problem

AI could accelerate the hunt for new physics, but sometimes it knows too much to see what’s right in front of it.
GitHub

Efficient Frequency-Domain Image Deraining with Contrastive Regularization (ECCV2024)

2024/09/25 Update：The code is now open, welcome to ask questions in the issue, we will try our best to solve errors and doubts 2024/09/26 Update: Pre-trained ...
IEEE

LWCDNet: A Lightweight Fully Convolution Network for Change Detection in Optical Remote Sensing Imagery

Abstract: Change detection (CD) is an important task in remote sensing image processing. The main research goal is to identify whether the target area has changed. Recently, the rise of deep learning ...
IEEE

Fast Space-Varying Convolution Using Matrix Source Coding With Applications to Camera Stray Light Reduction

Abstract: Many imaging applications require the implementation of space-varying convolution for accurate restoration and reconstruction of images. Here, we use the term space-varying convolution to ...
Frontiers

Detection Method of Citrus Psyllids With Field High-Definition Camera Based on Improved Cascade Region-Based Convolution Neural Networks

Citrus psyllid is the only insect vector of citrus Huanglongbing (HLB), which is the most destructive disease in the citrus industry. There is no effective treatment for HLB, so detecting citrus ...
Frontiers

Motor Imagery EEG Signal Recognition Using Deep Convolution Neural Network

Brain computer interaction (BCI) based on EEG can help patients with limb dyskinesia to carry out daily life and rehabilitation training. However, due to the low signal-to-noise ratio and large ...
acm.org

ImageNet Classification with Deep Convolutional Neural Networks

Five ILSVRC-2010 test images in the first column. Remaining columns show the training images that produce feature vectors in the last hidden layer with the smallest Euclidean distance from the feature ...