Visual and geographical data fusion to classify landmarks in geo-tagged images

High level semantic image recognition and classification is a challenging task and currently is a very active research domain. Computers struggle with the high level task of identifying objects and scenes within digital images accurately in unconstrained environments. In this paper, we present experiments that aim to overcome the limitations of computer vision algorithms by combining them with novel contextual based features to describe geo-tagged imagery. We adopt a machine learning based algorithm with the aim of classifying classes of geographical landmarks within digital images. We use community contributed image sets downloaded from Flickr and provide a thorough investigation, the results of which are presented in an evaluation section

Music, Myth and Motherland: Culturally Centered Music & Imagery

This study assessed ethnic identity in adults of Indian origin through Culturally Centered Music & Imagery (CCMI), a music-centered, psychotherapeutic technique that emphasizes socio-cultural context, identity and meaning. The purpose was to examine how participants’ native music, in the context of CCMI, could evoke identity-based imagery and assess ethnic identity in a globalized context. Five cisgender Indian men and women from Hindu backgrounds participated in one CCMI session each, including an interview and follow up discussions. The qualitative methodology of portraiture (Lawrence-Lightfoot, 1997) was used in this study. The results reveal how CCMI can access the cultural and ethnic unconscious, a relatively new area of consciousness in Jungian and GIM paradigms. The study also shows how CCMI can highlight the fluid and multiple nature of ethnic identity, revealing its intersection with other identities such as gender, sexual orientation, caste and religion. In addition, the data support the use of contextual and identity-based music selections in assisting participants to explore, recreate or gain a deeper understanding of their ethnic identity through image and metaphor. Major findings include new categories of ethnic identity such as Aesthetic, Ancestral, Philosophical, Mythological, Spiritual and Core Indian identities. Subthemes include experiences of Rebirth, Disconnection, Unconscious Divide, as well as other socio-cultural identities such as Kaleidoscopic, World Citizen and Global Nomad. These and other themes relate to American, global, spiritual, queer, socio-economic, caste, gendered, and individual contexts. The research also suggests that this technique may be effective in emotionally and psychologically supporting adults who are going through the process of immigration or acculturation

Learning to Read by Spelling: Towards Unsupervised Text Recognition

This work presents a method for visual text recognition without using any paired supervisory data. We formulate the text recognition task as one of aligning the conditional distribution of strings predicted from given text images, with lexically valid strings sampled from target corpora. This enables fully automated, and unsupervised learning from just line-level text-images, and unpaired text-string samples, obviating the need for large aligned datasets. We present detailed analysis for various aspects of the proposed method, namely - (1) impact of the length of training sequences on convergence, (2) relation between character frequencies and the order in which they are learnt, (3) generalisation ability of our recognition network to inputs of arbitrary lengths, and (4) impact of varying the text corpus on recognition accuracy. Finally, we demonstrate excellent text recognition accuracy on both synthetically generated text images, and scanned images of real printed books, using no labelled training examples

Women over 40, foreigners of color, and other missing persons in globalizing mediascapes: understanding marketing images as mirrors of intersectionality

Media diversity studies regularly invoke the notion of marketing images as mirrors of racism and sexism. This article develops a higher-order concept of marketing images as “mirrors of intersectionality.” Drawing on a seven-dimensional study of coverperson diversity in a globalizing mediascape, the emergent concept highlights that marketing images reflect not just racism and sexism, but all categorical forms of marginalization, including ableism, ageism, colorism, fatism, and heterosexism, as well as intersectional forms of marginalization, such as sexist ageism and racist multiculturalism. Fueled by the legacies of history, aspirational marketing logics, and an industry-wide distribution of discriminatory work, marketing images help to perpetuate multiple, cumulative, and enduring advantages for privileged groups and disadvantages for marginalized groups. In this sense, marketing images, as mirrors of intersectionality, are complicit agents in the structuration of inequitable societies

Women's Professional Identity Formation in the Free/Open Source Software Community

We examine the formation of women’s professional identity in a particular type of male-dominated domain, the free and open source software development communities, and more broadly in information technology. Through an ethnographic analysis of interviews and online forums discussions, we find that women experience two types of discrepancies or gaps that constitute obstacles in the process of identity formation: an image gap and an identity gap. We show the strategies employed by women as they attempt to bridge these gaps; we also find that some of these strategies, while tackling one gap, may also deepen the other.Gender; Identity Formation; Self-presentation