Research aims to standardize rock climbing route difficulty through machine learning techniques
Researchers have explored how integrating machine and deep learning techniques can create a standardized system for evaluating rock climbing routes to provide a difficulty grading scale that promotes inclusivity, accuracy and accessibility for all experience levels. The study found that the most successful approach for determining the difficulty of a rock-climbing route used route-centric, natural language processing methods.
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Researchers have explored how integrating machine and deep learning techniques can create a standardized system for evaluating rock climbing routes to provide a difficulty grading scale that promotes inclusivity, accuracy and accessibility for all experience levels. The study found that the most successful approach for determining the difficulty of a rock-climbing route used route-centric, natural language processing methods.
