Women in Artificial intelligence (AI)
This Special Issue, entitled "Women in Artificial Intelligence" includes 17 papers from leading women scientists. The papers cover a broad scope of research areas within Artificial Intelligence, including machine learning, perception, reasoning or planning, among others. The papers have ap...
Saved in:
Other Authors: | , |
---|---|
Format: | Electronic Book Chapter |
Language: | English |
Published: |
Basel
MDPI - Multidisciplinary Digital Publishing Institute
2022
|
Subjects: | |
Online Access: | DOAB: download the publication DOAB: description of the publication |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
MARC
LEADER | 00000naaaa2200000uu 4500 | ||
---|---|---|---|
001 | doab_20_500_12854_93766 | ||
005 | 20221117 | ||
003 | oapen | ||
006 | m o d | ||
007 | cr|mn|---annan | ||
008 | 20221117s2022 xx |||||o ||| 0|eng d | ||
020 | |a books978-3-0365-5532-4 | ||
020 | |a 9783036555324 | ||
020 | |a 9783036555317 | ||
040 | |a oapen |c oapen | ||
024 | 7 | |a 10.3390/books978-3-0365-5532-4 |c doi | |
041 | 0 | |a eng | |
042 | |a dc | ||
072 | 7 | |a TB |2 bicssc | |
072 | 7 | |a TBX |2 bicssc | |
100 | 1 | |a Valls, Aida |4 edt | |
700 | 1 | |a Gibert, Karina |4 edt | |
700 | 1 | |a Valls, Aida |4 oth | |
700 | 1 | |a Gibert, Karina |4 oth | |
245 | 1 | 0 | |a Women in Artificial intelligence (AI) |
260 | |a Basel |b MDPI - Multidisciplinary Digital Publishing Institute |c 2022 | ||
300 | |a 1 electronic resource (332 p.) | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
520 | |a This Special Issue, entitled "Women in Artificial Intelligence" includes 17 papers from leading women scientists. The papers cover a broad scope of research areas within Artificial Intelligence, including machine learning, perception, reasoning or planning, among others. The papers have applications to relevant fields, such as human health, finance, or education. It is worth noting that the Issue includes three papers that deal with different aspects of gender bias in Artificial Intelligence. All the papers have a woman as the first author. We can proudly say that these women are from countries worldwide, such as France, Czech Republic, United Kingdom, Australia, Bangladesh, Yemen, Romania, India, Cuba, Bangladesh and Spain. In conclusion, apart from its intrinsic scientific value as a Special Issue, combining interesting research works, this Special Issue intends to increase the invisibility of women in AI, showing where they are, what they do, and how they contribute to developments in Artificial Intelligence from their different places, positions, research branches and application fields. We planned to issue this book on the on Ada Lovelace Day (11/10/2022), a date internationally dedicated to the first computer programmer, a woman who had to fight the gender difficulties of her times, in the XIX century. We also thank the publisher for making this possible, thus allowing for this book to become a part of the international activities dedicated to celebrating the value of women in ICT all over the world. With this book, we want to pay homage to all the women that contributed over the years to the field of AI. | ||
540 | |a Creative Commons |f https://creativecommons.org/licenses/by/4.0/ |2 cc |4 https://creativecommons.org/licenses/by/4.0/ | ||
546 | |a English | ||
650 | 7 | |a Technology: general issues |2 bicssc | |
650 | 7 | |a History of engineering & technology |2 bicssc | |
653 | |a artificial intelligence | ||
653 | |a computer-aided diagnosis | ||
653 | |a computed tomography | ||
653 | |a lung cancer | ||
653 | |a deep learning | ||
653 | |a lung nodule detection | ||
653 | |a lung nodule segmentation | ||
653 | |a convolutional neural network | ||
653 | |a cellular automaton | ||
653 | |a reconstruction | ||
653 | |a complexity | ||
653 | |a optimization | ||
653 | |a high energy physics | ||
653 | |a Reddit | ||
653 | |a user-based model | ||
653 | |a polarization | ||
653 | |a local search optimization | ||
653 | |a hate speech | ||
653 | |a hate spread | ||
653 | |a countermeasures | ||
653 | |a social networks | ||
653 | |a opinion diffusion | ||
653 | |a education | ||
653 | |a deferring hate content | ||
653 | |a cyber activism | ||
653 | |a classical Arabic | ||
653 | |a short vowels | ||
653 | |a audio dataset | ||
653 | |a convolutional neural networks | ||
653 | |a regularization | ||
653 | |a machine learning | ||
653 | |a segmentation | ||
653 | |a clustering | ||
653 | |a forecasting | ||
653 | |a book copies | ||
653 | |a publishing industry | ||
653 | |a gamification | ||
653 | |a adaptive gamification | ||
653 | |a player types | ||
653 | |a computational finance | ||
653 | |a fuzzy logic | ||
653 | |a membership function | ||
653 | |a Type-1 fuzzy sets | ||
653 | |a T1FLS | ||
653 | |a Type-2 fuzzy sets | ||
653 | |a T2FLS | ||
653 | |a women | ||
653 | |a research | ||
653 | |a CURE | ||
653 | |a hierarchical clustering | ||
653 | |a cluster validity indices | ||
653 | |a Calinski-Harabasz index | ||
653 | |a bootstrapping | ||
653 | |a Industry 4.0 | ||
653 | |a 3D printing | ||
653 | |a cognitive states | ||
653 | |a mental workload | ||
653 | |a EEG analysis | ||
653 | |a neural networks | ||
653 | |a multimodal data fusion | ||
653 | |a peer assessment | ||
653 | |a multiagent system | ||
653 | |a probabilistic model | ||
653 | |a comparative analysis | ||
653 | |a Bayesian network | ||
653 | |a Artificial Intelligence | ||
653 | |a urban water cycle | ||
653 | |a hydrosocial urban cycle | ||
653 | |a urban political ecology | ||
653 | |a gender gap | ||
653 | |a equity | ||
653 | |a explainable AI | ||
653 | |a fuzzy rules | ||
653 | |a dominance-based rough set approach | ||
653 | |a diabetic retinopathy | ||
653 | |a AI | ||
653 | |a disease surveillance | ||
653 | |a pandemics | ||
653 | |a global public health | ||
653 | |a ethics | ||
653 | |a data | ||
653 | |a missing datasets | ||
653 | |a data-driven studies | ||
653 | |a women in artificial intelligence | ||
653 | |a women in data science | ||
653 | |a women in STEM | ||
653 | |a n/a | ||
856 | 4 | 0 | |a www.oapen.org |u https://mdpi.com/books/pdfview/book/6194 |7 0 |z DOAB: download the publication |
856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/93766 |7 0 |z DOAB: description of the publication |