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Transfer Learning with Convolutional Neural Networks for Rainfall Detection in Single Images
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Hydrology in a Changing World
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Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation
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An Experimental Introduction to the Theory of probability
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Measurements and Observations in the XXI century (MOXXI): innovation and multi-disciplinarity to sense the hydrological cycle
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Measurements of rainfall rates from videos
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ImageNet: A large-scale hierarchical image database
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Two-Class Weather Classification
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Some Studies in Machine Learning Using the Game of Checkers
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An Image Processing based Raindrop Parameter Estimation
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Imminent Nowcasting for Severe Rainfall Using Vertically Integrated Liquid Water Content Derived from X-Band Polarimetric Radar
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An enquiry into rainfall data measurement and processing for model use in urban hydrology
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RAINFALL RE-ESTIMATION ASSOCIATED WITH DIFFERENCES IN THE DETECTION TIME OF RAINFALL BETWEEN X-BAND MP RADAR AND RAINGAUGE
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Geospatial Methods and Tools for Natural Risk Management and Communications
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Rain Streaks Detection and Removal in Image based on Entropy Maximization and Background Estimation
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What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Computer Vision-Based Method for Rainfall Estimation Using Cctv Cameras and Smartphone Videos
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Degradation of Commercially Available Digital Camera Images Due to Variation of Rainfall Intensity in Outdoor Conditions
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Degradation of Commercially Available Digital Camera Images due to Variation of Rainfall Intensity in Outdoor Conditions
inferred← citeshttps://doi.org/10.1002/wat2.1678openalex-snapshot
A review of video‐based rainfall measurement methods
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Enhancing Image Quality Through Hybrid Sparse Deep Rain-Net: Integrating Convolutional Sparse Coding and Deep Image Prior
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STURM-FloodDepth: A deep learning pipeline for mapping urban flood depth using street-level and oblique aerial imagery
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AVFF-RI: an improved rainfall intensity measurement using common cameras
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Advancing Weather Image Classification Using Deep Convolutional Neural Networks
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Deep Learning-Based Rainfall Prediction Using Cloud Image Analysis
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Harnessing Data for Flood Prediction: A Systematic Review of Forecasting Techniques and Information Sources
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Optical Rainfall Measurement Using Orthogonal Dual-Camera Image Fusion and Tri-Class Segmentation
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Intercomparison and Assessment of Stand-Alone and Wavelet-Coupled Machine Learning Models for Simulating Rainfall-Runoff Process in Four Basins of Pothohar Region, Pakistan
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Intelligent Flood Scene Understanding Using Computer Vision-Based Multi-Object Tracking
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Rainfall intensity estimations based on degradation characteristics of images taken with commercial cameras
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