Search Results - (( java application bees algorithm ) OR ( framework segmentation learning algorithm ))
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Enhanced Deep Learning Framework for Fine-Grained Segmentation of Fashion and Apparel
Published 2022“…This work proposes a deep learning framework that can learn how to detect and segment clothing objects accurately. …”
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Framework for stream clustering of trajectories based on temporal micro clustering technique
Published 2018“…The temporal micro cluster data structure is proposed in CC_TRS algorithm to store the summarized information for each group of similar segments. …”
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A Reinforcement Learning Based Adaptive ROI Generation for Video Object Segmentation
Published 2021“…The primary focus of the current deep learning-based models is to learn the discriminative representations in the foreground over motion and appearance in small-term temporal segments. …”
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2TSS: Two-tier semantic segmentation framework with enhancement for hotspot detection of solar photovoltaic thermal images
Published 2025“…The proposed method is designed with two subsequent stages of segmentation models, including image pre-processing at the initial of the framework. …”
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A detailed description on unsupervised heterogeneous anomaly based intrusion detection framework
Published 2019“…More effort has been taken in utilizing the data mining and machine learning algorithms to construct anomaly based intrusion detection systems, but the dependency on the learned models that were built based on earlier network behaviour still exists, which restricts those methods in detecting new or unknown intrusions. …”
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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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Cooperative spectrum sensing based on machine learning in cognitive radio vehicular network / Mohammad Asif Hossain
Published 2022“…The tri-agent reinforcement learning (TA-RL) algorithm has been used by the segment spectrum agent (SSA) in this suggested CSS to make the global decision. …”
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Development of brain tumor segmentation of magnetic resonance imaging (MRI) using u-net deep learning
Published 2023“…This work demonstrated comparative performance and successful feasibility of implementing U-Net CNN architecture in an automated framework of brain tumor segmentations in Fluid-attenuated inversion recovery (FLAIR) MR Slices. …”
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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach
Published 2025“…This study presents a post-pandemic machine learning-based analytical framework specifically designed for Malaysia’s ecommerce market. …”
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Deep Reinforcement Learning Based Unmanned Aerial Vehicle (UAV) Control Using 3D Hand Gestures
Published 2022“…In this paper, we designed a hybrid framework, which is based on Reinforcement Learning and Deep Learning where the traditional electronic flight controller is replaced by using 3D hand gestures. …”
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Optimizing E-commerce inventory management using a machine-learning approach
Published 2025“…To address this issue, this study proposes an integrated machine-learning framework that combines predictive analytics and customer segmentation to improve forecasting precision and inventory control. …”
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Deep learning semantic segmentation for water level estimation using surveillance camera
Published 2021“…This work presented two well-established deep learning algorithms, DeepLabv3+ and SegNet networks, and evaluated their performances using several evaluation metrics. …”
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Development of river water level estimation from surveillance cameras for flood monitoring system using deep learning techniques
Published 2022“…Hence, deep learning technique was chosen for water segmentation procedure in this work. …”
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Optimising acoustic features for source mobile device identification using spectral analysis techniques / Mehdi Jahanirad
Published 2016“…Both models optimize acoustic features for source mobile device identification based on near-silent segments. The proposed feature sets along with selected feature extraction methods from the literature are analyzed and compared by using supervised learning techniques (i.e. support vector machines, nearest-neighbor, naïve Bayesian, neural network, logistic regression, and ensemble trees classifier), as well as unsupervised learning techniques (i.e. probabilistic-based and nearest-neighbor-based algorithms). …”
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Development of a CAD system for stroke diagnosis using machine learning on DWI-MRI images
Published 2025“…For classification, the system evaluates traditional machine learning algorithms like support vector machine (SVM) and k-nearest neighbor (KNN), alongside deep learning models such as convolutional neural network (CNN) and bilayered neural network (BNN). …”
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A selective approach for energy-aware video content adaptation decision-taking engine in android based smartphone
Published 2019“…The EnVADE algorithm uses selective mechanism. Selective mechanism means the video segmented into scenes and adaptation process is done based on the selected scenes. …”
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A selective approach for energy-aware video content adaptation decision-taking engine in android based smartphone
Published 2019“…The EnVADE algorithm uses selective mechanism. Selective mechanism means the video segmented into scenes and adaptation process is done based on the selected scenes. …”
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