Study on Rice Grain Mildewed Region Recognition Based on Microscopic Computer Vision and YOLO-v5 Model

Deep CNN-based damage classification of milled rice grains using a high-magnification image dataset

(2022) Bhupendra et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Deep Learning Segmentation in Bulk Grain Images for Prediction of Grain Market Quality

(2022) Sahand Assadzadeh et al.   Food and Bioprocess Technology

Computer-Assisted Real-Time Rice Variety Learning Using Deep Learning Network

(2022) Pandia Rajan Jeyaraj et al.   Rice Science

Convolutional Neural Networks in Computer Vision for Grain Crop Phenotyping: A Review

(2022) Ya-Hong Wang et al.   Agronomy-Basel

High-throughput soybean seeds phenotyping with convolutional neural networks and transfer learning

(2021) Si Yang et al.   Plant Methods

A review on various methods for recognition of urine particles using digital microscopic images of urine sediments

(2021) Suhail K. et al.   Biomedical Signal Processing and Control

Computer vision based food grain classification: A comprehensive survey

(2021) Henry O. Velesaca et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

A YOLO-Based Target Detection Model for Offshore Unmanned Aerial Vehicle Data

(2021) Zhenhua Wang et al.   Sustainability

Tea chrysanthemum detection under unstructured environments using the TC-YOLO model

(2021) Chao Qi et al.   EXPERT SYSTEMS WITH APPLICATIONS

Classifying maize kernels naturally infected by fungi using near-infrared hyperspectral imaging

(2020) Xuan Chu et al.   INFRARED PHYSICS & TECHNOLOGY

YOLO-face: a real-time face detector

(2020) Weijun Chen et al.   VISUAL COMPUTER

Colored rice quality inspection system using machine vision

(2019) Shumian Chen et al.   JOURNAL OF CEREAL SCIENCE

Development of an expert vision-based system for inspecting rice quality indices

(2018) S.H. Payman et al.   Quality Assurance and Safety of Crops & Foods

Deep Learning for Computer Vision: A Brief Review

(2018) Athanasios Voulodimos et al.   Computational Intelligence and Neuroscience

Computer vision and artificial intelligence in precision agriculture for grain crops: A systematic review

(2018) Diego Inácio Patrício et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Recognition of Mould Colony on Unhulled Paddy Based on Computer Vision using Conventional Machine-learning and Deep Learning Techniques

(2016) Ke Sun et al.   Scientific Reports

Microbial Prevalence on Freshly-Harvested Long-Grain Pureline, Hybrid, andMedium-Grain Rice Cultivars

(2015)   APPLIED ENGINEERING IN AGRICULTURE

Monitoring fungal growth on brown rice grains using rapid and non-destructive hyperspectral imaging

(2015) U. Siripatrawan et al.   INTERNATIONAL JOURNAL OF FOOD MICROBIOLOGY

Fungal Damage Detection in Wheat Using Short-Wave Near-Infrared Hyperspectral and Digital Colour Imaging

(2010) C.B. Singh et al.   INTERNATIONAL JOURNAL OF FOOD PROPERTIES

Moulds and mycotoxins in rice from the Swedish retail market

(2009) E. Fredlund et al.   Food Additives and Contaminants Part A-Chemistry Analysis Control Exposure & Risk Assessment