output
20162024
most citedMore Diverse Means Better: Multimodal Deep Learning Meets Remote Sensing Imagery Classification

1.4k citations

Showing cs.CVShow all

12 papers · 1 filter

cs.CV202129 cited

Nonlocal Patch-Based Fully-Connected Tensor Network Decomposition for Remote Sensing Image Inpainting

Wen-Jie Zheng, Xi-Le Zhao, Yu-Bang Zheng +1

Remote sensing image (RSI) inpainting plays an important role in real applications. Recently, fully-connected tensor network (FCTN) decomposition has been shown the remarkable abil…

cs.CV20218 cited

Goal-Oriented Gaze Estimation for Zero-Shot Learning

Yang Liu, Lei Zhou, Xiao Bai +4

Zero-shot learning (ZSL) aims to recognize novel classes by transferring semantic knowledge from seen classes to unseen classes. Since semantic knowledge is built on attributes sha…

cs.CV202129 cited

Source-free Domain Adaptation via Distributional Alignment by Matching Batch Normalization Statistics

Masato Ishii, Masashi Sugiyama

In this paper, we propose a novel domain adaptation method for the source-free setting. In this setting, we cannot access source data during adaptation, while unlabeled target data…

cs.CV2020

Leveraging Tacit Information Embedded in CNN Layers for Visual Tracking

Kourosh Meshgi, Maryam Sadat Mirzaei, Shigeyuki Oba

Different layers in CNNs provide not only different levels of abstraction for describing the objects in the input but also encode various implicit information about them. The activ…

cs.CV20206 cited

Learning from Multimodal and Multitemporal Earth Observation Data for Building Damage Mapping

Bruno Adriano, Naoto Yokoya, Junshi Xia +4

Earth observation technologies, such as optical imaging and synthetic aperture radar (SAR), provide excellent means to monitor ever-growing urban environments continuously. Notably…

cs.CV20201.4k cited

More Diverse Means Better: Multimodal Deep Learning Meets Remote Sensing Imagery Classification

Danfeng Hong, Lianru Gao, Naoto Yokoya +4

Classification and identification of the materials lying over or beneath the Earth's surface have long been a fundamental but challenging research topic in geoscience and remote se…