mlsanityData to 7 Oct 2026

Measuring the Ripeness of Fruit with Hyperspectral Imaging and Deep Learning

arXiv 2104.09808 ↗First posted 20 Apr 2021cs.CVcited by 12

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Abstract (arXiv)

We present a system to measure the ripeness of fruit with a hyperspectral camera and a suitable deep neural network architecture. This architecture did outperform competitive baseline models on the prediction of the ripeness state of fruit. For this, we recorded a data set of ripening avocados and kiwis, which we make public. We also describe the process of data collection in a manner that the adaption for other fruit is easy. The trained network is validated empirically, and we investigate the trained features. Furthermore, a technique is introduced to visualize the ripening process.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 8 of its 33 references that are in the map. First posted on arXiv 20 Apr 2021.

Builds on

8 of 33 references.

References · 8

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 2; 2023: 1; 2024: 2; 2025: 1; 2026: 5.

12 papers.

  1. 2022Wavelength-aware 2D Convolutions for Hyperspectral Imagingcited by 6
  2. 2021Tackling the Background Bias in Sparse Object Detection via Cropped Windowscited by 5
  3. 2023Hyperspectral Benchmark: Bridging the Gap between HSI Applications through Comprehensive Dataset and Pretrainingcited by 3
  4. 2024SpectralZoom: Efficient Segmentation with an Adaptive Hyperspectral Cameracited by 2
  5. 2022Automatic Monitoring of Fruit Ripening Rooms by UHF RFID Sensor Network and Machine Learningcited by 1
  6. 2026HyperVision: A Channel-Adaptive Ground-Based Hyperspectral Vision Pre-trained Backbonecited by 1
  7. 2024Cost-efficient Active Illumination Camera For Hyper-spectral Reconstructioncited by 0
  8. 2025Label Semantics for Robust Hyperspectral Image Classificationcited by 0
  9. 2026Adaptive Subspace Modeling With Functional Tucker Decompositioncited by 0
  10. 2026SSFT: A Lightweight Spectral-Spatial Fusion Transformer for Generic Hyperspectral Classificationcited by 0
  11. 2026Transfer learning RGB models to hyperspectral images with trainable tensor decompositionscited by 0
  12. 2026Fruit-HSNet: A Machine Learning Approach for Hyperspectral Image-Based Fruit Ripeness Predictioncited by 0