The Outcome of the 2021 IEEE GRSS Data Fusion Contest—Track MSD: Multitemporal Semantic Change Detection

Autor: Zhuohong Li, Fangxiao Lu, Hongyan Zhang, Lilin Tu, Jiayi Li, Xin Huang, Caleb Robinson, Nikolay Malkin, Nebojsa Jojic, Pedram Ghamisi, Ronny Hansch, Naoto Yokoya

Publikováno v: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 1643-1655 (2022)

We present here the scientific outcomes of the 2021 Data Fusion Contest (DFC2021) organized by the Image Analysis and Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society. DFC2021 was dedicated to research on geospatial a

Externí odkaz: https://doaj.org/article/b9d2f391bf1540638ea6087341fd972f

Global Land-Cover Mapping With Weak Supervision: Outcome of the 2020 IEEE GRSS Data Fusion Contest

Autor: Caleb Robinson, Kolya Malkin, Nebojsa Jojic, Huijun Chen, Rongjun Qin, Changlin Xiao, Michael Schmitt, Pedram Ghamisi, Ronny Hansch, Naoto Yokoya

Publikováno v: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 3185-3199 (2021)

This article presents the scientific outcomes of the 2020 Data Fusion Contest (DFC2020) organized by the Image Analysis and Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society. The 2020 Contest addressed the problem of a

Externí odkaz: https://doaj.org/article/528a0ede82f04100be73de48f671644d

Compositional Processing Emerges in Neural Networks Solving Math Problems

Autor: Jacob, Russin, Roland, Fernandez, Hamid, Palangi, Eric, Rosen, Nebojsa, Jojic, Paul, Smolensky, Jianfeng, Gao

Publikováno v: Cogsci

A longstanding question in cognitive science concerns the learning mechanisms underlying compositionality in human cognition. Humans can infer the structured relationships (e.g., grammatical rules) implicit in their sensory observations (e.g., audito

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::173ed512a2fcb24dae836fca790810c8
https://pubmed.ncbi.nlm.nih.gov/34617074

Multi-Label Learning from Single Positive Labels

Autor: Dan Morris, Oisin Mac Aodha, Elijah Cole, Titouan Lorieul, Nebojsa Jojic, Pietro Perona

Publikováno v: CVPR
Cole, E, Mac Aodha, O, Lorieul, T, Perona, P, Morris, D & Jojic, N 2021, Multi-Label Learning From Single Positive Labels . in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . Institute of Electrical and Electronics Engineers (IEEE), pp. 933-942, IEEE Conference on Computer Vision and Pattern Recognition 2021, 19/06/21 . https://doi.org/10.1109/CVPR46437.2021.00099

Predicting all applicable labels for a given image is known as multi-label classification. Compared to the standard multi-class case (where each image has only one label), it is considerably more challenging to annotate training data for multi-label

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::23d7c1c6049cd0def474d6b6665e08c1
https://doi.org/10.1109/cvpr46437.2021.00099

Studying word order through iterative shuffling

Autor: Nikolay Malkin, Sameera Lanka, Pranav Goel, Nebojsa Jojic

As neural language models approach human performance on NLP benchmark tasks, their advances are widely seen as evidence of an increasingly complex understanding of syntax. This view rests upon a hypothesis that has not yet been empirically tested: th

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e3b592845c866489dc37c2fbb9ca687f