Manzano et al., 2024 - Google Patents
YOLOv5-Based Image Processing for Pineapple Rind Defect DetectionManzano et al., 2024
- Document ID
- 3797102017175551945
- Author
- Manzano J
- Ea J
- Caya M
- Publication year
- Publication venue
- 2024 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)
External Links
Snippet
This study implemented YOLOv5 (You Only Look Once) as its algorithm to detect pineapple rind defects using known image processing techniques such as preprocessing and augmentation. Python language was used to integrate the YOLOv5 algorithm, and a …
- 235000007119 Ananas comosus 0 title abstract description 92
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6267—Classification techniques
- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
- G06K9/00268—Feature extraction; Face representation
- G06K9/00281—Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30244—Information retrieval; Database structures therefor; File system structures therefor in image databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Hasan et al. | Rice disease identification and classification by integrating support vector machine with deep convolutional neural network | |
Aguilar et al. | Grab, pay, and eat: Semantic food detection for smart restaurants | |
AU2020100953A4 (en) | Automated food freshness detection using feature deep learning | |
CN107578060B (en) | Method for classifying dish images based on depth neural network capable of distinguishing areas | |
Chen et al. | Chinesefoodnet: A large-scale image dataset for chinese food recognition | |
CN110211087B (en) | Sharable semiautomatic marking method for diabetic fundus lesions | |
Miriti | Classification of selected apple fruit varieties using Naive Bayes | |
Uy et al. | A durian variety identifier using canny edge and CNN | |
Monigari et al. | Plant leaf disease prediction | |
Nirale et al. | Analytical Study on IoT and Machine Learning based Grading and Sorting System for Fruits | |
Ramesh et al. | Real-time food-object detection and localization for indian cuisines using deep neural networks | |
Singh et al. | Apple Disease Classification Built on Deep Learning | |
Manzano et al. | YOLOv5-Based Image Processing for Pineapple Rind Defect Detection | |
Zhao et al. | A novel hyperspectral feature-extraction algorithm based on waveform resolution for raisin classification | |
Khandelwal et al. | Image Processing Based Quality Analyzer and Controller | |
Sahuri | Implementation of Deep Learning Methods in Detecting Disease on Chili Leaf | |
Zheng et al. | Study on tomato disease classification based on leaf image recognition based on deep learning technology | |
Kumar et al. | A Neoteric Procedure for Spotting and Segregation of Ailments in Mediciative Plants using Image Processing Techniques. | |
Thongpance et al. | Exploring ResNet-18 Estimation Design through Multiple Implementation Iterations and Techniques in Legacy Databases | |
Valarmathi et al. | Fruit Disease Prediction with Fertilizer Recommendation for Citrus Family using Deep Learning | |
Pradheep et al. | Fruit Disease Classification using Convolutional Neural Network | |
Yumang et al. | Magnolia Jackfruit Maturity Classification System Using Color Space Analysis | |
Gurumurthi et al. | Recognition of plant leaf diseases using CNN | |
Mehra | GuavaNet: A deep neural network architecture for automatic sensory evaluation to predict degree of acceptability for Guava by a consumer | |
EYADA et al. | DEVELOPMENT OF A DEEP LEARNING-BASED MOBILE APPLICATION TO DETECT FRESHNESS OF FRUITS |