Nature

Blind source separation and unmanned aerial vehicle classification using CNN with hybrid cross-channel and spatial attention module

The widespread misuse of drones has become a pressing concern for both public safety and privacy in recent years. The accurate identification and classification of these devices has become a practical ...
C&EN

Multimodal Image Fusion Workflow Incorporating MALDI Imaging Mass Spectrometry and Microscopy for the Study of Small Pharmaceutical Compounds

Department of Pharmaceutics, College of Pharmacy, University of Florida, Gainesville, Florida 32610, United States Department of Medicinal Chemistry, College of Pharmacy, University of Florida, ...
Nature

A fused multi-subfrequency bands and CBAM SSVEP-BCI classification method based on convolutional neural network

For the brain-computer interface (BCI) system based on steady-state visual evoked potential (SSVEP), it is difficult to obtain satisfactory classification performance for short-time window SSVEP ...
Frontiers

A CNN-Based Deep Learning Approach for SSVEP Detection Targeting Binaural Ear-EEG

This paper discusses a machine learning approach for detecting SSVEP at both ears with minimal channels. SSVEP is a robust EEG signal suitable for many BCI applications. It is strong at the visual ...
GitHub

Explainable AI: interpreting the classification performed by deep learning with LIME

This demo shows how to interpret the classification by CNN using LIME (Local Interpretable Model-agnostic Explanations) [1]. This demo was created based on [1], but the implementation might be a ...
Frontiers

Identifying Epilepsy Based on Deep Learning Using DKI Images

Epilepsy is a serious hazard to human health. Minimally invasive surgery is currently an extremely effective treatment to refractory epilepsy. However, it is challenging to localize the lesion for ...
GitHub

deep learning object detection

2018/9/18 - update all of recent papers and make some diagram about history of object detection using deep learning. 2018/9/26 - update codes of papers. (official and unofficial) 2018/october - update ...
C&EN

3D Molecular Representations Based on the Wave Transform for Convolutional Neural Networks

Convolutional neural networks (CNN) have been successfully used to handle three-dimensional data and are a natural match for data with spatial structure such as 3D molecular structures. However, a ...
PNAS

Emergent neuronal mechanisms mediating covert attention in convolutional neural networks

Cues predictive of target locations orient covert attention, improving perceptual performance. Studies have focused on attentional influences on neural activity, but how cues activate attention and ...