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Leaf condition analysis using convolutional neural network and vision transformer
Published 2024“…Through the use of a hybrid deep learning model that combines vision transformer and convolutional neural networks for classification, the algorithm can be optimized. …”
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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Deep plant: A deep learning approach for plant classification / Lee Sue Han
Published 2018“…They look for the procedures or algorithms that maximize the use of leaf databases for plant predictive modelling, but this results in leaf features which are liable to change with different leaf data and feature extraction techniques. …”
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Classification of Citrus (Rutaceae) by Using Image Processing
Published 2019“…This research will be conducted by using digital image processing approach based on the morphological features of leaf with the combination of gray level co-occurrence matrix (GLCM), Prewitt and Canny algorithm and training classification models by using support vector machine (SVM). …”
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Undergraduate Final Project Report -
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Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm
Published 2018“…During the field experiments, leaf samples of healthy (T1), mildly (T2), moderately (T3) and severely-infected (T4) palms were measured using a Minolta SPAD-502 chlorophyll meter and a SC-1 leaf Porometer to obtain relative leaf chlorophyll content and stomatal conductance, respectively. …”
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A novel framework for potato leaf disease detection using an efficient deep learning model
Published 2022“…Various experiments have been performed to confirm that our proposed algorithm is more consistent and proficient to detect and classify potato leaves diseases than existing models. …”
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A novel framework for potato leaf disease detection using an efficient deep learning model
Published 2022“…Various experiments have been performed to confirm that our proposed algorithm is more consistent and proficient to detect and classify potato leaves diseases than existing models. …”
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Classification of capsicum leaf disease from a complex cluster of leaves using an improved multiple layers ShuffleNet CNN model
Published 2023“…These models have achieved an average accuracy of classification. …”
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Comparative study on leaf disease identification using Yolo v4 and Yolo v7 algorithm
Published 2023“…The models are trained with individual leaf images shot under different ambience, which imparts robustness and versatility to the models. …”
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Classification model for hotspot occurrences using a decision tree method
Published 2011“…This work demonstrates the application of a decision tree algorithm, namely the C4.5 algorithm, to develop a classification model from forest fire data in the Rokan Hilir district, Indonesia. …”
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Mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm
Published 2014“…The algorithms were tested to classify the leaf samples into four levels of disease severity. …”
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Cornsense: leaf disease detection application / Iffah Fatinah Mohamad Nasir
Published 2025“…Utilizing YOLOv8 allows for real-time and accurate classification of corn leaf images into various disease categories. …”
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Classification model for chlorophyll content using CNN and aerial images
Published 2024“…Therefore, this study proposed a classification approach in developing a deep learning model to analyse the plant’s health condition without human intervention. …”
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Assessment of near-infrared and mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm plantation
Published 2013“…The results indicated that LDA-based model resulted in high average overall classification accuracies of 92% (leaf samples) and 94% (trunk samples) when mid-infrared absorbance spectra were analyzed. …”
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Deep learning detector for pests and plant disease recognition
Published 2020“…However, in this project, deep learning techniques are used in developing a model for diseases and pest detection in plants, and then train and test the model before eventually integrating the model into a mobile application. …”
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Final Year Project / Dissertation / Thesis -
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Application of genetic algorithm methods to optimize flowshop sequencing problem
Published 2008“…Genetic algorithm method was one of the methods that were widely used in solving optimization problem. …”
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Undergraduates Project Papers -
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