Report: Computer vision teams worldwide say projects are delayed by insufficient data

According to new research by Datagen, 99% of computer vision (CV) teams have had a machine learning (ML) project canceled due to insufficient training data. Delays, meanwhile, appear truly ubiquitous, with 100% of teams reporting experiencing significant project delays due to insufficient training data. The research also indicates that these training data challenges come in many forms and affect CV teams in near-equal measure. The top issues experienced by CV teams include poor annotation (48%), inadequate domain coverage (47%), and simple scarcity (44%). The scarcity of robust, domain-specific training data is only compounded by the fact that the field of computer vision is lacking many well-defined standards or best practices. When asked how training data is typically gathered at their organizations, respondents revealed a patchwork of sources and methodologies are being employed both across the field and within individual organizations.