Deep Domain Adaptation Approach for Classification of Disaster Images

[1]  Cornelia Caragea,et al.  Identifying Disaster Damage Images Using a Domain Adaptation Approach , 2019, ISCRAM.

[2]  Cornelia Caragea,et al.  Disaster Response Aided by Tweet Classification with a Domain Adaptation Approach , 2018 .

[3]  Qiang Yang,et al.  A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.

[4]  Victor S. Lempitsky,et al.  Unsupervised Domain Adaptation by Backpropagation , 2014, ICML.

[5]  Ramesh Nallapati,et al.  A Comparative Study of Methods for Transductive Transfer Learning , 2007 .

[6]  Keri K. Stephens,et al.  Using a combination of human insights and ‘deep learning’ for real-time disaster communication , 2019, Progress in Disaster Science.

[7]  Franco Turini,et al.  Time-Annotated Sequences for Medical Data Mining , 2007 .

[8]  Mei Wang,et al.  Deep Visual Domain Adaptation: A Survey , 2018, Neurocomputing.

[9]  Arlene Satuito,et al.  Determining Disaster Risk Management Priorities through a Neural Network-Based Text Classifier , 2018, 2018 International Symposium on Computer, Consumer and Control (IS3C).

[10]  Firoj Alam,et al.  Processing Social Media Images by Combining Human and Machine Computing during Crises , 2018, Int. J. Hum. Comput. Interact..

[11]  Hassan Sajjad,et al.  Rapid Classification of Crisis-Related Data on Social Networks using Convolutional Neural Networks , 2016, ICWSM 2016.

[12]  Cornelia Caragea,et al.  Twitter Mining for Disaster Response: A Domain Adaptation Approach , 2015, ISCRAM.

[13]  Leysia Palen,et al.  Microblogging during two natural hazards events: what twitter may contribute to situational awareness , 2010, CHI.

[14]  Firoj Alam,et al.  Domain Adaptation with Adversarial Training and Graph Embeddings , 2018, ACL.

[15]  Yoshua Bengio,et al.  How transferable are features in deep neural networks? , 2014, NIPS.

[16]  Carlos Castillo,et al.  AIDR: artificial intelligence for disaster response , 2014, WWW.

[17]  Andrew Zisserman,et al.  Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.

[18]  Kripabandhu Ghosh,et al.  Automatic Matching of Resource Needs and Availabilities in Microblogs for Post-Disaster Relief , 2018, WWW.

[19]  Muhammad Imran,et al.  Localizing and quantifying infrastructure damage using class activation mapping approaches , 2019, Social Network Analysis and Mining.

[20]  S. Natarajan,et al.  How social media can contribute during disaster events? Case study of Chennai floods 2015 , 2016, 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI).

[21]  Muhammad Imran,et al.  Social-EOC: Serviceability Model to Rank Social Media Requests for Emergency Operation Centers , 2018, 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

[22]  Muhammad Imran,et al.  Damage Assessment from Social Media Imagery Data During Disasters , 2017, 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

[23]  Firoj Alam,et al.  Descriptive and visual summaries of disaster events using artificial intelligence techniques: case studies of Hurricanes Harvey, Irma, and Maria , 2019, Behav. Inf. Technol..

[24]  Niloy Ganguly,et al.  Extracting Situational Information from Microblogs during Disaster Events: a Classification-Summarization Approach , 2015, CIKM.

[25]  Firoj Alam,et al.  CrisisMMD: Multimodal Twitter Datasets from Natural Disasters , 2018, ICWSM.