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121
Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis
Published 2023“…Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …”
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Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing
Published 2023“…This paper provides a comparative analysis of various metaheuristic load balancing algorithms for cloud computing based on performance factors i.e., Makespan time, degree of imbalance, response time, data center processing time, flow time, and resource utilization. …”
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Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle
Published 2025“…<p dir="ltr">This study presents an innovative solution for simultaneous energy optimization and dynamic yaw control of all-wheel-drive (AWD) electric vehicles (EVs) using deep reinforcement learning (DRL) techniques. To this end, three model-free DRL-based methods, based on deep deterministic policy gradient (DDPG), twin delayed deep deterministic policy gradient (TD3), and TD3 enhanced with curriculum learning (CL TD3), are developed for determining optimal yaw moment control and energy optimization online. …”
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A Fusion-Based Approach for Skin Cancer Detection Combining Clinical Images, Dermoscopic Images, and Metadata
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doctoralThesis -
126
A fast exact sequential algorithm for the partial digest problem
Published 2016“…Two types of simulated data, random and Zhang, are used to measure the efficiency of the algorithm. …”
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127
Use of Data Mining Techniques to Detect Fraud in Procurement Sector
Published 2022“…The method used in this research is a classification of models and algorithms used in data mining. All techniques also will be studied; they include clustering, tracking patterns, classifications and outlier detection. …”
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128
Cyberbullying Detection and Abuser Profile Identification on Social Media for Roman Urdu
Published 2024Subjects: -
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A comprehensive review of deep reinforcement learning applications from centralized power generation to modern energy internet frameworks
Published 2025“…<p>The energy internet (EI) is evolving toward decentralized, data-rich, and time-critical operation, where legacy optimization often fails to meet complexity, scalability, and real-time constraints. Deep reinforcement learning (DRL) offers a data-driven alternative that couples perception with sequential decision-making. …”
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131
Artificial Intelligence for the Prediction and Early Diagnosis of Pancreatic Cancer: Scoping Review
Published 2023Subjects: -
132
Deep Neural Networks for Electromagnetic Inverse Scattering Problems in Microwave Imaging
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doctoralThesis -
133
Autonomous 3D Deployment of Aerial Base Stations in Wireless Networks with User Mobility
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134
DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins
Published 2025“…ConclusionWe present the effectiveness of DeepRaman, an innovative architecture inspired by the Progressive Fourier Transform and integrated with the scalogram transformation method, in classifying raw SERS Raman spectral data from biological specimens with unparalleled accuracy relative to conventional machine learning algorithms. …”
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135
Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval
Published 2024“…Unfortunately, PCA’s reliability drops when data has nonlinear characteristics as industrial processes. …”
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136
Enhanced Deep Belief Network Based on Ensemble Learning and Tree-Structured of Parzen Estimators: An Optimal Photovoltaic Power Forecasting Method
Published 2021“…The meta-model layer exploits deep belief network to generate the final outputs. …”
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137
A Hybrid Transfer Learning Approach to Teeth Diagnosis Using Orthopantomogram Radiographs
Published 2024“…To showcase the performance of such algorithms, we propose two approaches for the task of teeth diagnosis utilizing Orthopantomograms (panoramic radiographs): 1) a direct classification approach; and 2) a hybrid approach that combines a deep learning model with a traditional classifier. …”
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