285 machine learning datasets
285 dataset results
A fundamental component of human vision is our ability to parse complex visual scenes and judge the relations between their constituent objects. AI benchmarks for visual reasoning have driven rapid progress in recent years with state-of-the-art systems now reaching human accuracy on some of these benchmarks. Yet, there remains a major gap between humans and AI systems in terms of the sample efficiency with which they learn new visual reasoning tasks. Humans' remarkable efficiency at learning has been at least partially attributed to their ability to harness compositionality -- allowing them to efficiently take advantage of previously gained knowledge when learning new tasks. Here, we introduce a novel visual reasoning benchmark, Compositional Visual Relations (CVR), to drive progress towards the development of more data-efficient learning algorithms. We take inspiration from fluidic intelligence and non-verbal reasoning tests and describe a novel method for creating compositions of abs
This dataset called Indoor Lodz University of Technology Point Cloud Dataset (InLUT3D) is a point cloud set tailored for real object classification and both semantic and instance segmentation tasks. Comprising of 321 scans, some areas in the dataset are covered by multiple scans. All of them are captured using the Leica BLK360 scanner.
The Fields2Benhmark dataset is a collection of 350 agricultural fields in vector format manually selected to test agricultural coverage path planning algorithms.
<h1>Huawei University Challenge Competition 2021</h1>
Expedia ™️ main customer service number is 1-800-Expedia ™️ or +1-888⇌»⇌829⇌0881 [US-Expedia ™️] or +1-888⇌»⇌829⇌0881 [UK-Expedia ™️] OTA (Live Person), available 24/7. This guide explains how to contact Expedia ™️ customer service effectively through phone, chat, and email options, including tips for minimizing wait times.