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.
Fruit-HSNet: A Machine Learning Approach for Hyperspectral Image-Based Fruit Ripeness Prediction
Efrei Research Lab, Paris Panthéon-Assas University（巴黎先贤祠-阿萨斯大学埃弗雷研究所）；Institute of Applied Computer Science, Lodz University of Technology（罗兹理工大学应用计算机科学研究所）
Foundation Model-Based Apple Ripeness and Size Estimation for Selective Harvesting
Department of Mechanical Engineering, Michigan State University（机械工程系，密歇根州立大学）；Department of Electrical and Computer Engineering, Michigan State University（电气与计算机工程系，密歇根州立大学）；Department of Computer Science and Engineering, Michigan State University（计算机科学与工程系，密歇根州立大学）；United States Department of Agriculture Agricultural Research Service（美国农业部农业研究服务）
Facilitated machine learning for image-based fruit quality assessment
Empa, Swiss Federal Laboratories for Materials Science and Technology（瑞士联邦材料科学与技术实验室（Empa））；Swiss Data Science Center, ETH Zurich and EPFL（瑞士数据科学中心（苏黎世联邦理工学院与洛桑联邦理工学院共建））；ETH Zurich（苏黎世联邦理工学院）
A survey on computational spectral reconstruction methods from RGB to hyperspectral imaging
University of Chinese Academy of Sciences（中国科学院大学）；Xidian University（西安电子科技大学）；King Abdullah University of Science and Technology（阿卜杜拉国王科技大学）；Institute of Information Engineering, Chinese Academy of Sciences（中国科学院信息工程研究所）；Princeton University（普林斯顿大学）；Vrije Universiteit Brussel（布鲁塞尔自由大学）
Integrating Feature Selection and Machine Learning for Nitrogen Assessment in Grapevine Leaves using In-Field Hyperspectral Imaging
organization= Center for Precision；Automated Agricultural Systems , addressline= Washington State University , city= Prosser , postcode= 99350 , state= WA , country= USA；organization= Biological \& Environmental Engineering Department , addressline= Cornell University , city= Ithaca , postcode= 14853 , state= NY , country= USA；organization= Fruit Research；Extension Center , addressline= The Penn State University , city= Biglerville , postcode= 17307 , state= PA , country= USA；organization= School of Business；Technology , addressline= Curry College , city= Milton , postcode= 02186 , state= MA , country= USA；organization= Department of Viticulture；Enology , addressline= Washington State University , city= Prosser , postcode= 99350 , state= WA , country= USA；Genetic Improvement Research Unit (HCPGIRU) , city= Corvallis , postcode= 973300 , state= OR , country= USA；organization= Mid-Columbia Agricultural Research；Extension Center , addressline = Oregon State University , city= Corvallis , postcode= 97031 , state= OR , country= USA；organization= Department of Plant Sciences , addressline = University of Tennessee, Institute of Agriculture , city= Knoxville , postcode= 37996 , state= TN , country= USA
