research
∙
04/30/2023
Interpretability of Machine Learning: Recent Advances and Future Prospects
The proliferation of machine learning (ML) has drawn unprecedented inter...
share
research
∙
03/20/2022
Vision Transformer with Convolutions Architecture Search
Transformers exhibit great advantages in handling computer vision tasks....
research
∙
10/28/2021
ODMTCNet: An Interpretable Multi-view Deep Neural Network Architecture for Image Feature Representation
This work proposes an interpretable multi-view deep neural network archi...
research
∙
09/08/2021
Visual Sensation and Perception Computational Models for Deep Learning: State of the art, Challenges and Prospects
Visual sensation and perception refers to the process of sensing, organi...
research
∙
03/23/2021
Enhanced Gradient for Differentiable Architecture Search
In recent years, neural architecture search (NAS) methods have been prop...
research
∙
03/09/2021
A Discriminative Vectorial Framework for Multi-modal Feature Representation
Due to the rapid advancements of sensory and computing technology, multi...
research
∙
02/28/2021
A Complete Discriminative Tensor Representation Learning for Two-Dimensional Correlation Analysis
As an effective tool for two-dimensional data analysis, two-dimensional ...
research
∙
02/28/2021
Discriminative Multiple Canonical Correlation Analysis for Information Fusion
In this paper, we propose the Discriminative Multiple Canonical Correlat...
research
∙
02/27/2021
Online Behavioral Analysis with Application to Emotion State Identification
In this paper, we propose a novel discriminative model for online behavi...
research
∙
01/31/2021
MLMA-Net: multi-level multi-attentional learning for multi-label object detection in textile defect images
For the sake of recognizing and classifying textile defects, deep learni...
research
∙
12/21/2020
Optimizing Deep Neural Networks through Neuroevolution with Stochastic Gradient Descent
Deep neural networks (DNNs) have achieved remarkable success in computer...
research
∙
12/20/2020
A hybrid deep-learning approach for complex biochemical named entity recognition
Named entity recognition (NER) of chemicals and drugs is a critical doma...
research
∙
09/20/2020
Predicting Geographic Information with Neural Cellular Automata
This paper presents a novel framework using neural cellular automata (NC...
research
∙
06/02/2020
Comparing and Integrating US COVID-19 Daily Data from Multiple Sources: A County-Level Dataset with Local Characteristics
Over the past several months, the outbreak of COVID-19 has been expandin...
research
∙
05/19/2020
Dynamic Partial Removal: A Neural Network Heuristic for Large Neighborhood Search
This paper presents a novel neural network design that learns the heuris...
research
∙
04/29/2020
Spatiotemporal Dynamics, Nowcasting and Forecasting of COVID-19 in the United States
In response to the ongoing public health emergency of COVID-19, we inves...
research
∙
02/20/2020
Learn to Design the Heuristics for Vehicle Routing Problem
This paper presents an approach to learn the local-search heuristics tha...
research
∙
11/04/2019
Superpixel-Based Background Recovery from Multiple Images
In this paper, we propose an intuitive method to recover background from...
research
∙
11/04/2019
Field of View Extension in Computed Tomography Using Deep Learning Prior
In computed tomography (CT), data truncation is a common problem. Images...
research
∙
10/20/2017
Detecting Online Hate Speech Using Context Aware Models
In the wake of a polarizing election, the cyber world is laden with hate...
research
∙
10/20/2017
