Quality control of apples by means of convolutional neural networks - Comparison of bruise detection by color images and near-infrared images
暂无分享,去创建一个
Michael Freitag | Benjamin Staar | Juan Daniel Arango | Adil Maqsood Baig | M. Freitag | Benjamin Staar
[1] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[2] Michael Freitag,et al. Deep Learning-Based Pose Estimation of Apples for Inspection in Logistic Centers Using Single-Perspective Imaging , 2019, Processes.
[3] Chu Zhang,et al. Detection of Subtle Bruises on Winter Jujube Using Hyperspectral Imaging With Pixel-Wise Deep Learning Method , 2019, IEEE Access.
[4] Kilian Q. Weinberger,et al. Densely Connected Convolutional Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[5] Li Fei-Fei,et al. ImageNet: A large-scale hierarchical image database , 2009, CVPR.
[6] Jeremy Howard,et al. fastai: A Layered API for Deep Learning , 2020, Inf..
[7] Ning Wang,et al. Early detection of apple bruises on different background colors using hyperspectral imaging , 2008 .
[8] Ning Wang,et al. Bruise Detection of Apples Using Hyperspectral Imaging , 2010 .
[9] R. Lu,et al. Predicting bruise susceptibility of ‘Golden Delicious’ apples using hyperspectral scattering technique , 2016 .
[10] Lei Zhang,et al. Gradient Centralization: A New Optimization Technique for Deep Neural Networks , 2020, ECCV.
[11] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[12] Hamid R. Arabnia,et al. Apple classification based on surface bruises using image processing and neural networks , 2002 .
[13] Kamran Rousta,et al. Life cycle assessment of supermarket food waste , 2017 .
[14] P. Baranowski,et al. Detection of early bruises in apples using hyperspectral data and thermal imaging , 2012 .
[15] Yuzhen Lu,et al. Detection of Surface and Subsurface Defects of Apples Using Structured- Illumination Reflectance Imaging with Machine Learning Algorithms , 2018 .
[16] G. M. Hyde,et al. Non-contact bruise detection in apples by thermal imaging , 2003 .
[17] Leslie N. Smith,et al. A disciplined approach to neural network hyper-parameters: Part 1 - learning rate, batch size, momentum, and weight decay , 2018, ArXiv.
[18] Wouter Saeys,et al. Real-time pixel based early apple bruise detection using short wave infrared hyperspectral imaging in combination with calibration and glare correction techniques , 2016 .
[19] Geoffrey E. Hinton,et al. Rectified Linear Units Improve Restricted Boltzmann Machines , 2010, ICML.
[20] S. Karthikeyan,et al. Survey of Grading Process for Agricultural Foods by Using Artificial Intelligence Technique , 2018, 2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA).
[21] Wenqian Huang,et al. Detection of early bruises on peaches (Amygdalus persica L.) using hyperspectral imaging coupled with improved watershed segmentation algorithm , 2018 .
[22] Natalia Gimelshein,et al. PyTorch: An Imperative Style, High-Performance Deep Learning Library , 2019, NeurIPS.
[23] Wenqian Huang,et al. Development of a multispectral imaging system for online detection of bruises on apples , 2015 .
[24] Liyuan Liu,et al. On the Variance of the Adaptive Learning Rate and Beyond , 2019, ICLR.
[25] Zenghui Wang,et al. Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review , 2017, Neural Computation.
[26] Geoffrey E. Hinton,et al. Lookahead Optimizer: k steps forward, 1 step back , 2019, NeurIPS.
[27] Karthik Kuchangi Jothi Prakash,et al. Spoilage Detection in Raspberry Fruit Based on Spectral Imaging Using Convolutional Neural Networks , 2018 .
[28] Ning Wang,et al. Detecting chilling injury in Red Delicious apple using hyperspectral imaging and neural networks , 2009 .
[29] Michael Freitag,et al. Orientation detection of fruits by means of convolutional neural networks and laser line projection for the automation of fruit packing systems , 2020 .