Search Results for author:
Found 14 papers, 1 papers with code
AccessShare: Co-designing Data Access and Sharing with Blind People
Blind people are often called to contribute image data to datasets for AI innovation with the hope for future accessibility and inclusion.
"We are at the mercy of others' opinion": Supporting Blind People in Recreational Window Shopping with AI-infused Technology
In this paper, we investigate the information needs, challenges, and current approaches blind people have to recreational window shopping to inform the design of existing wayfinding and navigation technology for supporting blind shoppers in exploration and serendipitous discovery.
Examining the Values Reflected by Children during AI Problem Formulation
Understanding how children design and what they value in AI interfaces that allow them to explicitly train their models such as teachable machines, could help increase such activities' impact and guide the design of future technologies.
Blind Users Accessing Their Training Images in Teachable Object Recognizers
We explore how blind participants (N=12) interact with MyCam and the descriptors through an evaluation study in their homes.
Data Representativeness in Accessibility Datasets: A Meta-Analysis
We examine the current state of representation within datasets sourced by people with disabilities by reviewing publicly-available information of 190 datasets, we call these accessibility datasets.
MyMove: Facilitating Older Adults to Collect In-Situ Activity Labels on a Smartwatch with Speech
Current activity tracking technologies are largely trained on younger adults' data, which can lead to solutions that are not well-suited for older adults.
Exploring Machine Teaching with Children
Iteratively building and testing machine learning models can help children develop creativity, flexibility, and comfort with machine learning and artificial intelligence.
Pedestrian Detection with Wearable Cameras for the Blind: A Two-way Perspective
Blind people have limited access to information about their surroundings, which is important for ensuring one's safety, managing social interactions, and identifying approaching pedestrians.
Hand-Priming in Object Localization for Assistive Egocentric Vision
Egocentric vision holds great promises for increasing access to visual information and improving the quality of life for people with visual impairments, with object recognition being one of the daily challenges for this population.
Crowdsourcing the Perception of Machine Teaching
Teachable interfaces can empower end-users to attune machine learning systems to their idiosyncratic characteristics and environment by explicitly providing pertinent training examples.
Sign Language Recognition, Generation, and Translation: An Interdisciplinary Perspective
Developing successful sign language recognition, generation, and translation systems requires expertise in a wide range of fields, including computer vision, computer graphics, natural language processing, human-computer interaction, linguistics, and Deaf culture.
Cultural Vocal Bursts Intensity Prediction
Sign Language Recognition
+1
