research
∙
09/21/2023
MoDA: Leveraging Motion Priors from Videos for Advancing Unsupervised Domain Adaptation in Semantic Segmentation
Unsupervised domain adaptation (UDA) is an effective approach to handle ...
share
research
∙
07/16/2023
PrestigeBFT: Revolutionizing View Changes in BFT Consensus Algorithms with Reputation Mechanisms
This paper proposes PrestigeBFT, a novel leader-based BFT consensus algo...
research
∙
01/27/2023
Dual-View Selective Instance Segmentation Network for Unstained Live Adherent Cells in Differential Interference Contrast Images
Despite recent advances in data-independent and deep-learning algorithms...
research
∙
01/15/2023
V-Guard: An Efficient Permissioned Blockchain for Achieving Consensus under Dynamic Memberships in V2X Networks
This paper presents V-Guard, a new permissioned blockchain that achieves...
research
∙
07/19/2022
ML-BPM: Multi-teacher Learning with Bidirectional Photometric Mixing for Open Compound Domain Adaptation in Semantic Segmentation
Open compound domain adaptation (OCDA) considers the target domain as th...
research
∙
06/01/2022
Labeling Where Adapting Fails: Cross-Domain Semantic Segmentation with Point Supervision via Active Selection
Training models dedicated to semantic segmentation requires a large amou...
research
∙
04/07/2022
Reaching Consensus in the Byzantine Empire: A Comprehensive Review of BFT Consensus Algorithms
Byzantine fault-tolerant (BFT) consensus algorithms are at the core of p...
research
∙
10/13/2021
Attentive and Contrastive Learning for Joint Depth and Motion Field Estimation
Estimating the motion of the camera together with the 3D structure of th...
research
∙
07/26/2021
Transductive Maximum Margin Classifier for Few-Shot Learning
Few-shot learning aims to train a classifier that can generalize well wh...
research
∙
07/26/2021
Temporal Alignment Prediction for Few-Shot Video Classification
The goal of few-shot video classification is to learn a classification m...
research
∙
05/27/2021
Learning Structures for Deep Neural Networks
In this paper, we focus on the unsupervised setting for structure learni...
research
∙
05/25/2021
We Know What You Want: An Advertising Strategy Recommender System for Online Advertising
Advertising expenditures have become the major source of revenue for e-c...
research
∙
12/09/2020
Two-phase Pseudo Label Densification for Self-training based Domain Adaptation
Recently, deep self-training approaches emerged as a powerful solution t...
research
∙
06/24/2020
Affinity Fusion Graph-based Framework for Natural Image Segmentation
This paper proposes an affinity fusion graph framework to effectively co...
research
∙
04/16/2020
Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision
Convolutional neural network-based approaches have achieved remarkable p...
research
∙
08/19/2019
Learning to Advertise for Organic Traffic Maximization in E-Commerce Product Feeds
Most e-commerce product feeds provide blended results of advertised prod...
research
∙
04/17/2019
Variational Prototyping-Encoder: One-Shot Learning with Prototypical Images
In daily life, graphic symbols, such as traffic signs and brand logos, a...
research
∙
11/13/2018
PanJoin: A Partition-based Adaptive Stream Join
In stream processing, stream join is one of the critical sources of perf...
research
∙
02/27/2017