63 citations · 128 across the 34 of their papers we have counts for
10 papers · 1 filter
AI-Based Energy Transportation Safety: Pipeline Radial Threat Estimation Using Intelligent Sensing System
Chengyuan Zhu, Yiyuan Yang, Kaixiang Yang +3
The application of artificial intelligence technology has greatly enhanced and fortified the safety of energy pipelines, particularly in safeguarding against external threats. The…
Consistent123: Improve Consistency for One Image to 3D Object Synthesis
Haohan Weng, Tianyu Yang, Jianan Wang +4
Large image diffusion models enable novel view synthesis with high quality and excellent zero-shot capability. However, such models based on image-to-image translation have no guar…
Alzheimer's Disease Prediction via Brain Structural-Functional Deep Fusing Network
Qiankun Zuo, Junren Pan, Shuqiang Wang
Fusing structural-functional images of the brain has shown great potential to analyze the deterioration of Alzheimer's disease (AD). However, it is a big challenge to effectively f…
Rethinking Client Drift in Federated Learning: A Logit Perspective
Yunlu Yan, Chun-Mei Feng, Mang Ye +5
Federated Learning (FL) enables multiple clients to collaboratively learn in a distributed way, allowing for privacy protection. However, the real-world non-IID data will lead to c…
High-Similarity-Pass Attention for Single Image Super-Resolution
Jian-Nan Su, Min Gan, Guang-Yong Chen +2
Recent developments in the field of non-local attention (NLA) have led to a renewed interest in self-similarity-based single image super-resolution (SISR). Researchers usually used…
Online Learning Under A Separable Stochastic Approximation Framework
Min Gan, Xiang-xiang Su, Guang-yong Chen +1
We propose an online learning algorithm for a class of machine learning models under a separable stochastic approximation framework. The essence of our idea lies in the observation…
Towards Precise Weakly Supervised Object Detection via Interactive Contrastive Learning of Context Information
Qi Lai, ChiMan Vong
Weakly supervised object detection (WSOD) aims at learning precise object detectors with only image-level tags. In spite of intensive research on deep learning (DL) approaches over…
Robust Saliency-Aware Distillation for Few-shot Fine-grained Visual Recognition
Haiqi Liu, C. L. Philip Chen, Xinrong Gong +1
Recognizing novel sub-categories with scarce samples is an essential and challenging research topic in computer vision. Existing literature addresses this challenge by employing lo…
Properties and Potential Applications of Random Functional-Linked Types of Neural Networks
Guang-Yong Chen, Yong-Hang Yu, Min Gan +2
Random functional-linked types of neural networks (RFLNNs), e.g., the extreme learning machine (ELM) and broad learning system (BLS), which avoid suffering from a time-consuming tr…
ConvBLS: An Effective and Efficient Incremental Convolutional Broad Learning System for Image Classification
Chunyu Lei, C. L. Philip Chen, Jifeng Guo +1
Deep learning generally suffers from enormous computational resources and time-consuming training processes. Broad Learning System (BLS) and its convolutional variants have been pr…