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1
Development of lung cancer prediction system using meta-heuristic optimized deep learning model
Published 2023“…Finally, the classification is implemented using an ensemble classifier, deep learning instantaneously trained a neural network and an Autoencoder-based Recurrent Neural Network (ARNN) classification algorithm. …”
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2
Unleashing the power of Manta Rays Foraging Optimizer: A novel approach for hyper-parameter optimization in skin cancer classification
Published 2025“…Empirical evaluations on diverse datasets (ISIC, PH2, HAM10000) showcase the significant superiority of the MRFO-based model over conventional optimization algorithms. …”
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3
RLMD-PA: A Reinforcement Learning-Based Myocarditis Diagnosis Combined with a Population-Based Algorithm for Pretraining Weights
Published 2024journal::journal article -
4
Image-based air quality estimation using convolutional neural network optimized by genetic algorithms: A multi-dataset approach
Published 2025“…This paper proposes a new approach using convolutional neural networks with genetic algorithms for estimating air quality directly from images. …”
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Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah
Published 2021“…Based on investigation different architecture and parameter, the suitable deep learning model has been presented to get optimize best result and testing time. …”
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6
Detection of corneal arcus using rubber sheet and machine learning methods
Published 2019“…The benchmark of the classification algorithm for CA is needed to analyze the optimal output of the algorithm. …”
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7
Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images
Published 2024“…For segmentation, the first proposed algorithm is based on the boundary condition model, which is tested over the ISIC dataset and achieved 96% of accuracy. …”
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8
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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9
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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10
Evaluating Adan vs. Adam: an analysis of optimizer performance in deep learning
Published 2025“…Based on these results, this paper aims to provide insights into the strengths and limitations of each optimizer, highlighting the importance of considering task-specific requirements when selecting an optimization algorithm for deep learning models.…”
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Proceeding Paper -
11
Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…The combination of gist, MTH and SIFT features increased the performance of image identification and showed 49% accuracy. 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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12
A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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13
Detecting lung cancer region from CT image using meta-heuristic optimized segmentation approach
Published 2022“…In this paper, the butterfly optimization algorithm-based K-means clustering (BOAKMC) method is introduced for reducing CT image segmentation uncertainty. …”
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Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data
Published 2016“…The developed DT algorithm was applied to object-based classifications in the first study area. …”
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A joint Bayesian optimization for the classification of fine spatial resolution remotely sensed imagery using object-based convolutional neural networks
Published 2022“…A Bayesian technique was used to find the best parameters for the multiresolution segmentation (MRS) algorithm while the CNN model learns the image features at different layers, achieving joint optimization. …”
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The classification of wink-based eeg signals by means of transfer learning models
Published 2021“…Whilst it was observed that the optimized k-NN model based on the aforesaid pipeline could achieve a classification accuracy of 100% for the training, validation, and tes t data. …”
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A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal
Published 2019“…Features are then enhanced by using Tree-based feature selection to reduce the size of each feature and, therefore, enhance classification performance. …”
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Diabetic retinopathy detection using fusion of textural and optimized convolutional neural network features / Uzair Ishtiaq
Published 2024“…A Convolutional Neural Network (CNN) model was created from scratch for this study. Combining Local Binary Patterns (LBP) based texture features and deep learning features resulted in the creation of the fused features vector which was then optimized using Binary Dragonfly Algorithm (BDA) and Sine Cosine Algorithm (SCA). …”
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19
Deep learning-based item classification for retail automation
Published 2025“…Real-time processing was achieved through the integration of object detection algorithms like YOLO and image segmentation techniques. …”
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Final Year Project / Dissertation / Thesis -
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Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying
Published 2019“…Based on the final denoised images, the model has proven its reliability, in terms of both visual quality and quantitative evaluation. …”
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