Results 221 to 230 of about 530,080 (274)

Experimental evidence on consumers' willingness to pay in the sustainable fashion industry. [PDF]

Sci Rep
Cascavilla A, Caferra R, Morone A, Morone P.   +3 more
europepmc   +1 more source

Robust Distributed High-Dimensional Regression: A Convoluted Rank Approach. [PDF]

Entropy (Basel)
Wu M.
europepmc   +1 more source

Brand public opinion data analysis method based on deep learning. [PDF]

PLoS One
Li M, Chung W.
europepmc   +1 more source

Explainable AI-driven depression detection from social media using natural language processing and black box machine learning models. [PDF]

Front Artif Intell
Hameed S, Nauman M, Akhtar N, Fayyaz MAB, Nawaz R.   +4 more
europepmc   +1 more source

A visual SLAM loop closure detection method based on lightweight siamese capsule network. [PDF]

Sci Rep
Zhou Y, Sun M.
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A Machine Learning Approach for Identifying People With Neuroinfectious Diseases in Electronic Health Records: Algorithm Development and Validation.

JMIR Med Inform
Singh A, Sartipi S, Sun H, Milde R, Turley N, Quinn C, Harrold GK, Gillani RL, Turbett SE, Das S, Zafar S, Fernandes M, Westover MB, Mukerji SS.   +13 more
europepmc   +1 more source

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Bag-of-Words Similarity in eXplainable AI

2022
eXplainable AI (XAI) does not only lie in the interpretation of the rules generated by AI systems, but also in the evaluation and selection, among many rules automatically generated by large datasets, of those that are more relevant and meaningful for domain experts.
Narteni S, Ferretti M, Rampa V, Mongelli M   +3 more
openaire   +2 more sources

Improving Bag-Of-Words

Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers, 2018
Bag-of-Words (BoW) is one of the important techniques for activity recognition. Instead of dividing a continuous sensor streams into sliding windows with fixed time duration, it builds activity recognition models using histograms of primitive motion symbols.
Ming Zeng, Tong Yu, Ole J. Mengshoel, Helen Qin, Chris Lee, John Paul Shen   +5 more
openaire   +1 more source

Beyond bag of words

Proceedings of the 21st ACM international conference on Multimedia, 2013
Due to the semantic gap, the low-level features are not able to semantically represent images well. Besides, traditional semantic related image representation may not be able to cope with large inter class variations and are not very robust to noise.
Chunjie Zhang, Shuhui Wang, Chao Liang, Jing Liu, Qingming Huang, Haojie Li, Qi Tian   +6 more
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Bag of visual words revisited

Proceedings of the Tenth International Workshop on Multimedia Data Mining, 2010
Visual information retrieval systems have gained importance due to the increasing amount of available digital multimedia data. Local features employing a bag of words approach from text retrieval have outperformed global features and have enhanced retrieval performance in large data sets. In this paper we conduct an exploratory study revisiting the bag
Marian Kogler, Mathias Lux
openaire   +1 more source