Автор: Sunderason Sanjukta Название: Partisan Aesthetics: Modern Art and India`s Long Decolonization ISBN: 1503612996 ISBN-13(EAN): 9781503612990 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 4389.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Partisan Aesthetics explores art's entanglements with histories of war, famine, mass politics and displacements that marked late-colonial and postcolonial India. Introducing "partisan aesthetics" as a conceptual grid, the book identifies ways in which art became political through interactions with left-wing activism during the 1940s, and the afterlives of such interactions in post-independence India. Using an archive of artists and artist collectives working in Calcutta from these decades, Sanjukta Sunderason argues that artists became political not only as reporters, organizers and cadre of India's Communist Party, or socialist fellow travelers, but through shifting modes of political participations and dissociations. Unmooring questions of Indian modernism from its hitherto dominant harnesses to national or global affiliations, Sunderason activates, instead, distinctly locational histories that refract transnational currents. She analyzes largely unknown and dispersed archives—drawings, diaries, posters, periodicals, and pamphlets, alongside paintings and prints—and insists that art as archive is foundational to understanding modern art's socialist affiliations during India's long decolonization. By bringing together expanding fields of South Asian art, global modernisms, and Third World cultures, Partisan Aesthetics generates a new narrative that combines political history of Indian modernism, social history of postcolonial cultural criticism, and intellectual history of decolonization.
Автор: Sunderason Sanjukta Название: Partisan Aesthetics: Modern Art and India`s Long Decolonization ISBN: 1503611949 ISBN-13(EAN): 9781503611948 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 17556.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Partisan Aesthetics explores art's entanglements with histories of war, famine, mass politics and displacements that marked late-colonial and postcolonial India. Introducing "partisan aesthetics" as a conceptual grid, the book identifies ways in which art became political through interactions with left-wing activism during the 1940s, and the afterlives of such interactions in post-independence India. Using an archive of artists and artist collectives working in Calcutta from these decades, Sanjukta Sunderason argues that artists became political not only as reporters, organizers and cadre of India's Communist Party, or socialist fellow travelers, but through shifting modes of political participations and dissociations. Unmooring questions of Indian modernism from its hitherto dominant harnesses to national or global affiliations, Sunderason activates, instead, distinctly locational histories that refract transnational currents. She analyzes largely unknown and dispersed archives—drawings, diaries, posters, periodicals, and pamphlets, alongside paintings and prints—and insists that art as archive is foundational to understanding modern art's socialist affiliations during India's long decolonization. By bringing together expanding fields of South Asian art, global modernisms, and Third World cultures, Partisan Aesthetics generates a new narrative that combines political history of Indian modernism, social history of postcolonial cultural criticism, and intellectual history of decolonization.
Автор: Rik Das, Siddhartha Bhattacharyya, Sudarshan Nandy Название: Machine Learning Applications: Emerging Trends ISBN: 3110608537 ISBN-13(EAN): 9783110608533 Издательство: Walter de Gruyter Цена: 18586.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
The publication is attempted to address emerging trends in machine learning applications. Recent trends in information identification have identified huge scope in applying machine learning techniques for gaining meaningful insights. Random growth of unstructured data poses new research challenges to handle this huge source of information. Efficient designing of machine learning techniques is the need of the hour. Recent literature in machine learning has emphasized on single technique of information identification. Huge scope exists in developing hybrid machine learning models with reduced computational complexity for enhanced accuracy of information identification. This book will focus on techniques to reduce feature dimension for designing light weight techniques for real time identification and decision fusion. Key Findings of the book will be the use of machine learning in daily lives and the applications of it to improve livelihood. However, it will not be able to cover the entire domain in machine learning in its limited scope. This book is going to benefit the research scholars, entrepreneurs and interdisciplinary approaches to find new ways of applications in machine learning and thus will have novel research contributions. The lightweight techniques can be well used in real time which will add value to practice.
Описание: This book brings together theoretical, methodological and policy-relevant contributions by leading researchers on international child poverty.
