1.

Record Nr.

UNINA990005548690403321

Autore

Pierleoni, G.

Titolo

Ercolano / G. Pierleoni

Pubbl/distr/stampa

Milano, : Societa editrice Dante Alighieri di Albrighi, Segati & Co., [1927]

Descrizione fisica

6-48 p. ; 27 cm

Locazione

FLFBC

Collocazione

ARCH. X MISC. 12 (03)

Lingua di pubblicazione

Italiano

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Estr. dall'Annuario del R. Liceo Ginnasio G. Garibaldi in Napoli, anno III, 1926-27

2.

Record Nr.

UNINA9910729299903321

Autore

Blanchard Lynda-ann

Titolo

Ending War, Building Peace

Pubbl/distr/stampa

Sydney : , : Sydney University Press, , 2010

©2009

ISBN

9781743328323

174332832X

9781743321133

1743321139

Edizione

[1st ed.]

Descrizione fisica

1 online resource (197 pages)

Altri autori (Persone)

ChanLeah

Soggetti

Peace-building

Nonviolence

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia



Nota di contenuto

ENDING WAR, BUILDING PEACE -- Ending war, building peace --   More than conference proceedings --   Collaborative dialogue --     References -- Thinking war, crafting peace: a future for Iraq and civil liberties in Australia --   The fascination with violence and with war --   A lesson from poetry: when will they ever learn --   Thinking and crafting peace --   Peace settlement and humanitarian service --   And civil liberties in Australia --   Back to Iraq --     References -- The fascination with violence -- The venerated and unexamined violence in everyday life --   Commemorated violence --   Sacrifice --   Money in war --   Junk politics --   Ur-fascism --   Divine justice --   Final thoughts --     References -- Iraq, six years on: the human consequences of a dirty war --   A web of illusions --   Body count: no place to hide --   What is to be done? --     References -- The human and environmental costs of the Iraq and other wars --   Human security costs

Sommario/riassunto

The US-led invasion and occupation of Iraq led to more than a million people being killed, displaced five million from their homes and shattered countless more lives. It was a colossal, premeditated war crime. Leaders of governments in the countries responsible for this enormity seek to minimise and forget about it: to 'move on'. We must not let them, because they want to retain the option of making the same political decisions, condemning more innocent people to death, somewhere else in the future.



3.

Record Nr.

UNINA9910865233003321

Autore

Zhang Zheng (College teacher)

Titolo

Binary Representation Learning on Visual Images : Learning to Hash for Similarity Search / / by Zheng Zhang

Pubbl/distr/stampa

Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024

ISBN

9789819721122

9789819721115

Edizione

[1st ed. 2024.]

Descrizione fisica

1 online resource (210 pages)

Disciplina

621.367

Soggetti

Information storage and retrieval systems

Image processing

Artificial intelligence - Data processing

Information Storage and Retrieval

Image Processing

Data Science

Sistemes d'informació

Processament d'imatges

Intel·ligència artificial

Llibres electrònics

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Chapter 1. Introduction -- Chapter 2. Scalable Supervised Asymmetric Hashing -- Chapter 3. Inductive Structure Consistent Hashing -- Chapter 4. Probability Ordinal-preserving Semantic Hashing -- Chapter 5. Ordinal-preserving Latent Graph Hashing -- Chapter 6. Deep Collaborative Graph Hashing -- Chapter 7. Semantic-Aware Adversarial Training -- Index.

Sommario/riassunto

This book introduces pioneering developments in binary representation learning on visual images, a state-of-the-art data transformation methodology within the fields of machine learning and multimedia. Binary representation learning, often known as learning to hash or hashing, excels in converting high-dimensional data into compact binary codes meanwhile preserving the semantic attributes and



maintaining the similarity measurements. The book provides a comprehensive introduction to the latest research in hashing-based visual image retrieval, with a focus on binary representations. These representations are crucial in enabling fast and reliable feature extraction and similarity assessments on large-scale data. This book offers an insightful analysis of various research methodologies in binary representation learning for visual images, ranging from basis shallow hashing, advanced high-order similarity-preserving hashing, deep hashing, as well as adversarial and robust deep hashing techniques. These approaches can empower readers to proficiently grasp the fundamental principles of the traditional and state-of-the-art methods in binary representations, modeling, and learning. The theories and methodologies of binary representation learning expounded in this book will be beneficial to readers from diverse domains such as machine learning, multimedia, social network analysis, web search, information retrieval, data mining, and others.