Machine Learning and Remix: Self-training Selectivity in Digital Art Practice

2021 ◽  
pp. 191-204
Author(s):  
Eduardo Navas
Keyword(s):  
Machine Learning ◽  
Digital Art ◽  
Art Practice

Paradigm integration of fine art training for would-be professionals of art at high school at theory and local experience

2021 ◽  
Vol 7 (3C) ◽  
pp. 720-729
Author(s):  
Mykola Pichkur ◽  
Halyna Sotska ◽  
Andrii Hordash ◽  
Liliia Poluden ◽  
Iryna Patsaliuk
Keyword(s):  
Fine Arts ◽  
Fine Art ◽  
Digital Art ◽  
Educational Institutions ◽  
Art Practice ◽  
Higher Educational Institutions ◽  
Local Experience ◽  
Different Types ◽  
Higher Educational ◽  
Practice Development

In accordance with historic analysis, the article considers the valued traditional and innovative fine arts studios of artists of different generations; they help to identify specific artistic features of artists of different generations who create artistic works of the information world. We describe the genesis of digital art practice development and demonstrate its influence on the renovation of classic fine art classification system via the digital works of different types and genres. The limits of artistic amateur field as a factor of professional and profane blurring in an artist’s personality are clarified. The new concept of “digital paradigm of fine art training at higher educational institutions” is proposed in the article as an innovative method of specific subjects studying. Methodology of professional skills development while designing digital works for students of artistic profession at higher education was justified and the results of local experience of its implementation at higher educational institutions of Ukraine were described.

scholarly journals Bodily relations and reciprocity in the art of Sonia Khurana

2017 ◽  
Vol 29 (4) ◽  
pp. 255-274
Author(s):  
Leon Wainwright
Keyword(s):  
The Body ◽  
Digital Art ◽  
Radical Politics ◽  
New Delhi ◽  
Art Practice ◽  
Public Expectations ◽  
Art Practices ◽  
Ontological Turn ◽  
Discursive Field ◽  
Affective Relations

This article explores the significance of the ‘somatic’ and ‘ontological turn’ in locating the radical politics articulated in the contemporary performance, installation, video and digital art practices of New Delhi-based artist, Sonia Khurana (b. 1968). Since the late 1990s, Khurana has fashioned a range of artworks that require new sorts of reciprocal and embodied relations with their viewers. While this line of art practice suggests the need for a primarily philosophical mode of inquiry into an art of the body, such affective relations need to be historicised also in relation to a discursive field of ‘difference’ and public expectations about the artist’s ethnic, gendered and national identity. Thus, this intimate, visceral and emotional field of inter- and intra-action is a novel contribution to recent transdisciplinary perspectives on the gendered, social and sentient body that in turn prompts a wider debate on the ethics of cultural commentary and art historiography.

Renderings of Digital Art

Leonardo ◽  
2002 ◽  
Vol 35 (5) ◽  
pp. 471-484 ◽  
Author(s):  
Christiane Paul
Keyword(s):  
New Media ◽  
New Technology ◽  
Historical Context ◽  
Digital Art ◽  
Art Practice ◽  
Artistic Practice ◽  
Interactive Installation ◽  
Hybrid Nature ◽  
Net Art ◽  
Selection Of

This essay identifies the current qualifier of choice, “new media,” by explaining how this term is used to describe digital art in various forms. Establishing a historical context, the author highlights the pioneer exhibitions and artists who began working with new technology and digital art as early as the late 1960s and early 1970s. The article proceeds to articulate the shapes and forms of digital art, recognizing its broad range of artistic practice: music, interactive installation, installation with network components, software art, and purely Internet-based art. The author examines the themes and narratives specific to her selection of artwork, specifically interactive digital installations and net art. By addressing these forms, the author illustrates the hybrid nature of this medium and the future of this art practice.

scholarly journals Prototyping Machine Learning Through Diffractive Art Practice

2021 ◽  
Author(s):  
Hugo Scurto ◽  
Baptiste Caramiaux ◽  
Frederic Bevilacqua
Keyword(s):  
Machine Learning ◽  
Art Practice

scholarly journals A Japanese Approach to Haptic/Multimodal Art Practice and Perception

2015 ◽  
Vol 8 (1) ◽  
Author(s):  
Emilia Sosnowska
Keyword(s):  
Visual Culture ◽  
Cultural Context ◽  
East Asian ◽  
Theoretical Framework ◽  
Digital Art ◽  
Art Practice ◽  
Interactive Art ◽  
Culture Theory ◽  
Asian Philosophy ◽  
The World

This paper reflects a fraction of research which sets out to examine the complex constructions and debates underpinning visual culture theory, and assesses its adequacy as the main theoretical framework with which to engage in contemporary interactive art. The treatment presents digital art in Japan with its roots in traditional East Asian philosophy giving the senses a prominent role in perceiving the world and enabling perfect symbiosis between humans and machines. This paper points out the expansion of this culturally and traditionally inspired spirituality from its natural and cultural context to contemporary digitally mediated environments. This is accomplished through an analysis of digital interactive work by specific artists located in Japan, such as Kumiko Kushiyama, Masaki Fujihata and Ryota Kuwakubo.

scholarly journals Rhizomatic Remediation: Adaptation in a Web-Based Art Praxis During Time(s) of Crises

2020 ◽  
pp. 58-73
Author(s):  
Noah Travis Phillips
Keyword(s):  
Digital Art ◽  
Art Practice ◽  
Subjective Experiences ◽  
Art Making ◽  
Web Based ◽  
Personal Experiences ◽  
Virtual Exhibition

Willingness and the ability to adapt is vital in time(s) of crises. Remediation provides one novel and useful example of adaptation in contemporary digital art. This study explores the personal experiences of an art practice moving to virtual exhibition spaces, both by choice and as a response to multiple simultaneous crises (pandemic, environmental, racial, and democractic). This research reflects on three distinct examples of individual, subjective experiences of art making and exhibiting during this sudden shift. Each example highlights different approaches and possibilities, and examines similarities and contrasts in scales (local, national. and international) as well as more specific forms of remediation and relocation. Key findings include the different forms of remediation (different ways the art is translated for digital presentation) as well as the value of postinternet aesthetics, posthuman metamorphosis, and the nonsite. These themes help narrate these experiences and reflect more on these scenarios in ways that might be useful to other artists, curators, creative thinkers and practitioners. A suggestion is made that these groups would benefit from recognizing the value of rhizomatic (multi-centered, interrelated, and inclusive) approaches that include active remediation and adaptation.

scholarly journals Hear and See: End-to-end sound classification and visualization of classified sounds

2018 ◽  
Author(s):  
Thomas Miano
Keyword(s):  
Machine Learning ◽  
Digital Media ◽  
Digital Art ◽  
Machine Learning Techniques ◽  
Classification Task ◽  
Scientific Instrument ◽  
Sound Classification ◽  
Art Form ◽  
Learning Techniques ◽  
End To End

Machine learning is a field of study that uses computational and statistical techniques to enable computers to learn. When machine learning is applied, it functions as an instrument that can solve problems or expand knowledge about the surrounding world. Increasingly, machine learning is also an instrument for artistic expression in digital and non-digital media. While painted art has existed for thousands of years, the oldest digital art is less than a century old. Digital media as an art form is a relatively nascent, and the practice of machine learning in digital art is even more recent. Across all artistic media, a piece is powerful when it can captivate its consumer. Such captivation can be elicited through through a wide variety of methods including but not limited to distinct technique, emotionally evocative communication, and aesthetically pleasing combinations of textures. This work aims to explore how machine learning can be used simultaneously as a scientific instrument for understanding the world and as an artistic instrument for inspiring awe. Specifically, our goal is to build an end-to-end system that uses modern machine learning techniques to accurately recognize sounds in the natural environment and to communicate via visualization those sounds that it has recognized. We validate existing research by finding that convolutional neural networks, when paired with transfer learning using out-of-domain data, can be successful in mapping an image classification task to a sound classification task. Our work offers a novel application where the model used for performant sound classification is also used for visualization in an end-to-end, sound-to-image system.

Data visualization as creative art practice

2018 ◽  
Vol 17 (3) ◽  
pp. 299-312 ◽  
Author(s):  
Qi Li
Keyword(s):  
Big Data ◽  
Data Visualization ◽  
Information Visualization ◽  
Digital Art ◽  
Art Practice ◽  
Creative Potential ◽  
Creative Practice ◽  
Creative Art ◽  
Digital Artists

This article begins by tracing the evolution of data visualization from the fields of aesthetics to areas of creative practice, arguing that the emergence of big data presents creative potential for digital artists. Whereas conventional information visualization emphasizes the effective understanding of data, aesthetics considers the possibility that visualization can enhance the experience of data and support the acquisition of knowledge. In expressing an artistic intent or form, data-based creative practices synthesize and build upon techniques in communications and aesthetics. The article provides a review of recent digital art projects involving big data and suggests further directions for creative practice in an era of data proliferation.

Sign in / Sign up

Export Citation Format

Share Document