A Comprehensive Review of Crop Yield Prediction Using Machine Learning Approaches With Special Emphasis on Palm Oil Yield Prediction

Rashid, Mamunur; Bari, Bifta Sama; Yusup, Yusri; Kamaruddin, Mohamad Anuar; Khan, Nuzhat

doi:10.1109/access.2021.3075159

Cited by 105 publications

(24 citation statements)

References 200 publications

(207 reference statements)

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“…More overfitting issues often complicates general machine learning models. Intensive network structure optimization may address the issues of the local minima and overriding by DNNs [ 80 , 81 ]. Deep learning is a machine learning-based approach that educates computers to accomplish tasks similar to those performed by humans.…”

Section: Significant Research Work On Hand Gesture Recognitionmentioning

confidence: 99%

A Structured and Methodological Review on Vision-Based Hand Gesture Recognition System

et al. 2022

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Researchers have recently focused their attention on vision-based hand gesture recognition. However, due to several constraints, achieving an effective vision-driven hand gesture recognition system in real time has remained a challenge. This paper aims to uncover the limitations faced in image acquisition through the use of cameras, image segmentation and tracking, feature extraction, and gesture classification stages of vision-driven hand gesture recognition in various camera orientations. This paper looked at research on vision-based hand gesture recognition systems from 2012 to 2022. Its goal is to find areas that are getting better and those that need more work. We used specific keywords to find 108 articles in well-known online databases. In this article, we put together a collection of the most notable research works related to gesture recognition. We suggest different categories for gesture recognition-related research with subcategories to create a valuable resource in this domain. We summarize and analyze the methodologies in tabular form. After comparing similar types of methodologies in the gesture recognition field, we have drawn conclusions based on our findings. Our research also looked at how well the vision-based system recognized hand gestures in terms of recognition accuracy. There is a wide variation in identification accuracy, from 68% to 97%, with the average being 86.6 percent. The limitations considered comprise multiple text and interpretations of gestures and complex non-rigid hand characteristics. In comparison to current research, this paper is unique in that it discusses all types of gesture recognition techniques.

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Section: Significant Research Work On Hand Gesture Recognitionmentioning

confidence: 99%

A Structured and Methodological Review on Vision-Based Hand Gesture Recognition System

et al. 2022

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“…This review does not mention algorithms for predicting palm oil yields and breeding. [44] An overview of existing ML models for predicting crop yields. Various performance metrics are employed to assess the effectiveness of various strategies.…”

Section: Referencementioning

confidence: 99%

A Review of an Artificial Intelligence Framework for Identifying the Most Effective Palm Oil Prediction

et al. 2022

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Machine Learning (ML) offers new precision technologies with intelligent algorithms and robust computation. This technology benefits various agricultural industries, such as the palm oil sector, which possesses one of the most sustainable industries worldwide. Hence, an in-depth analysis was conducted, which is derived from previous research on ML utilisation in the palm oil in-dustry. The study provided a brief overview of widely used features and prediction algorithms and critically analysed current the state of ML-based palm oil prediction. This analysis is extended to the ML application in the palm oil industry and a comparison of related studies. The analysis was predicated on thoroughly examining the advantages and disadvantages of ML-based palm oil prediction and the proper identification of current and future agricultural industry challenges. Potential solutions for palm oil prediction were added to this list. Artificial intelligence and ma-chine vision were used to develop intelligent systems, revolutionising the palm oil industry. Overall, this article provided a framework for future research in the palm oil agricultural industry by highlighting the importance of ML.

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“…Subsequently, ML features are reviewed for automatic fruit grading with the help of image processing [23]. Recently, Rashid et al reviewed ML application for yield prediction of different crops, including oil palm [24]. From the reviewed literature, it is observed that present studies did not systematically search the literature in most cases.…”

Section: Introductionmentioning

confidence: 96%

Oil Palm and Machine Learning: Reviewing One Decade of Ideas, Innovations, Applications, and Gaps

et al. 2021

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Machine learning (ML) offers new technologies in the precision agriculture domain with its intelligent algorithms and strong computation. Oil palm is one of the rich crops that is also emerging with modern technologies to meet global sustainability standards. This article presents a comprehensive review of research dedicated to the application of ML in the oil palm agricultural industry over the last decade (2011–2020). A systematic review was structured to answer seven predefined research questions by analysing 61 papers after applying exclusion criteria. The works analysed were categorized into two main groups: (1) regression analysis used to predict fruit yield, harvest time, oil yield, and seasonal impacts and (2) classification techniques to classify trees, fruit, disease levels, canopy, and land. Based on defined research questions, investigation of the reviewed literature included yearly distribution and geographical distribution of articles, highly adopted algorithms, input data, used features, and model performance evaluation criteria. Detailed quantitative–qualitative investigations have revealed that ML is still underutilised for predictive analysis of oil palm. However, smart systems integrated with machine vision and artificial intelligence are evolving to reform oil palm agri-business. This article offers an opportunity to understand the significance of ML in the oil palm agricultural industry and provides a roadmap for future research in this domain.

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A Comprehensive Review of Crop Yield Prediction Using Machine Learning Approaches With Special Emphasis on Palm Oil Yield Prediction

Cited by 105 publications

References 200 publications

A Structured and Methodological Review on Vision-Based Hand Gesture Recognition System

A Structured and Methodological Review on Vision-Based Hand Gesture Recognition System

A Review of an Artificial Intelligence Framework for Identifying the Most Effective Palm Oil Prediction

Oil Palm and Machine Learning: Reviewing One Decade of Ideas, Innovations, Applications, and Gaps

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