Customer-obsessed science
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November 6, 2025A new approach to reducing carbon emissions reveals previously hidden emission “hotspots” within value chains, helping organizations make more detailed and dynamic decisions about their future carbon footprints.
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Featured news
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Journal of Applied Instructional Design2024Innovations in digital, interactive learning resources are increasingly being produced for online learning or e-learning. One area that is growing as a result of the increase in learning resources is computer-based simulations. Interactive computer simulations and simulators for education can offer similar traditional hands-on opportunities for learners to engage in learning activities. However, less is
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BMVC 20242024Understanding product dimensions can be challenging, hindering individuals from accurately visualizing how items will fit and look within their spaces. Addressing this, we present a novel automated approach to overlay dimensional lines onto product images, empowering users to understand each subcomponent’s size and scale. Our proposed multi-stage approach uses 3 key components: 3DBoundDetector to identify
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2024This paper addresses the failure detection and recovery problem in visual-inertial based Simultaneous Localization and Mapping (SLAM) systems for large-scale indoor environments. Camera and Inertial Measurement Unit (IMU) are popular choices for SLAM in many robotics tasks (e.g., navigation) due to their complementary sensing capabilities and low cost. However, vision has inherent challenges even in well-lit
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ACM SUI 20242024Point cloud annotation plays a pivotal role in computer vision and machine learning by facilitating the creation of volumetric annotations in 3D space. While prior research has explored point cloud annotation in VR environments, its practical implementation in space-constrained office settings, where data annotation is typically conducted, remains an open question. In this paper, we introduce Annorama,
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Language Resources and Evaluation2024In Artificial Intelligence research, perspectivism is an approach to machine learning that aims at leveraging data annotated by different individuals in order to model varied perspectives that influence their opinions and world view. We present the first survey of datasets and methods relevant to perspectivism in Natural Language Processing (NLP). We review datasets in which individual annotator labels
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