يعرض 261 - 280 نتائج من 311 نتيجة بحث عن 'differences ((modeling algorithm) OR (scheduling algorithm))', وقت الاستعلام: 0.08s تنقيح النتائج
  1. 261

    Practical Multiple Node Failure Recovery in Distributed Storage Systems حسب Itani, M.

    منشور في 2016
    "…Fast convergence validates the efficacy of our algorithms for different system parameters. Simulation results are shown to be close to optimal for the case of newly arriving blocks.…"
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    conferenceObject
  2. 262

    Artificial intelligence-based methods for fusion of electronic health records and imaging data حسب Farida Mohsen (16994682)

    منشور في 2022
    "…In our analysis, a typical workflow was observed: feeding raw data, fusing different data modalities by applying conventional machine learning (ML) or deep learning (DL) algorithms, and finally, evaluating the multimodal fusion through clinical outcome predictions. …"
  3. 263

    Performance Prediction Using Classification حسب MOOLIYIL, GITA

    منشور في 2019
    "…A comprehensive evaluation requires that multiple models with different algorithms were analyzed using key performance measures. …"
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  4. 264

    Depthwise Separable Convolutions and Variational Dropout within the context of YOLOv3 حسب Chakar, Joseph

    منشور في 2020
    "…Deep learning algorithms have demonstrated remarkable performance in many sectors and have become one of the main foundations of modern computer-vision solutions. …"
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    conferenceObject
  5. 265

    Diagnostic test accuracy of AI-assisted mammography for breast imaging: a narrative review حسب Daksh Dave (17949239)

    منشور في 2025
    "…Although AI models have shown promising improvements in sensitivity and specificity, challenges such as algorithmic bias, interpretability, and the generalizability of models across diverse populations remain. …"
  6. 266

    The Effects of Data Mining on Small Businesses in Dubai حسب AlMutawa, Rasha

    منشور في 2011
    "…While there are numerous studies on the best data mining models and their uses, even on certain industries, this study focuses on the applications more than the algorithms and models and their usefulness for small businesses specifically. …"
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  7. 267

    Precision nutrition: A systematic literature review حسب Daniel Kirk (17302798)

    منشور في 2021
    "…As such, recent research has applied machine learning algorithms, tools, and techniques in precision nutrition for different purposes. …"
  8. 268

    Cyberbullying Detection in Arabic Text using Deep Learning حسب ALBAYARI, REEM RAMADAN SA’ID

    منشور في 2023
    "…The proposed hybrid model improves the accuracy of all the studied datasets and can be integrated into different social media sites to automatically detect cyberbullying from Arabic social media posts. …"
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  9. 269

    Automatic Recognition of Poets for Arabic Poetry using Deep Learning Techniques (LSTM and Bi-LSTM) حسب AL SHOUBAKI, HAMZA YOUNIS

    منشور في 2024
    "…We also explore a range of algorithms, including traditional classifiers and deep learning models, to determine and select the most suitable and accurate models of identifying poets' names from the verses. …"
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  10. 270

    The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review حسب Zainab Jan (17306614)

    منشور في 2021
    "…The most commonly used data belonged to the clinical category (19, 58%). We identified different machine learning models used in the selected studies, including classification models (18, 55%), regression models (5, 16%), model-based clustering methods (2, 6%), natural language processing (1, 3%), clustering algorithms (1, 3%), and deep learning–based models (3, 9%). …"
  11. 271

    Enhancing e-learning through AI: advanced techniques for optimizing student performance حسب Rund Mahafdah (21399854)

    منشور في 2024
    "…The practical results obtained by implementing machine learning and deep learning models, such as convolutional neural networks (CNN) and recurrent neural networks (RNN), show substantial enhancements in forecasting different performance metrics. …"
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    Comparative Study on Arabic Text Classification: Challenges and Opportunities حسب Abualigah, Laith

    منشور في 2022
    "…There have been great improvements in web technology over the past years which heavily loaded the Internet with various digital contents of different fields. This made finding certain text classification algorithms that fit a specific language or a set of languages a difficult task for researchers. …"
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  15. 275

    Diabetic Sensorimotor Polyneuropathy Severity Classification Using Adaptive Neuro Fuzzy Inference System حسب Fahmida Haque (16896489)

    منشور في 2021
    "…Patients have been classified into four classes: Absent, Mild, Moderate, and Severe. The model accuracy was validated with the results from different machine learning algorithms. …"
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  18. 278

    Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis حسب Hassan, Ali

    منشور في 2023
    "…We experiment with multiple attackers—Text-bugger, Text-fooler, PWWS—on several architectures—MLP, CNN, LSTM, Hybrid CNN-RNN, BERT—trained for different classification tasks—IMDB sentiment classification, fake-news classification, AG news topic classification—under different threat models—Con-Detect-blind attacks, Con-Detect-aware attacks, and Con-Detect-adaptive attacks—and show that Con-Detect can reduce the attack success rate (ASR) of different attacks from 100% to as low as 0% for the best cases and ≈70% for the worst case. …"
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    article
  19. 279

    An intelligent approach to predicting the effect of nanoparticle mixture ratio, concentration and temperature on thermal conductivity of hybrid nanofluids حسب Ifeoluwa Wole-Osho (14151315)

    منشور في 2020
    "…A polynomial correlation model, the adaptive neuro-fuzzy inference system model and an artificial neural network model optimised with three different learning algorithms. …"
  20. 280

    Real-Time Social Robot’s Responses to Undesired Interactions Between Children and their Surroundings حسب Ahmad Yaser Alhaddad (7017434)

    منشور في 2022
    "…Additionally, we evaluate the performance of the best developed model with children. Machine learning algorithms experiments showed that XGBoost achieved the best performance across all metrics (e.g., accuracy of 90%) and provided fast predictions (i.e., 0.004 s) for the test samples. …"