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1
A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass
منشور في 2025"…By synthesizing findings across various data sources and model architectures, we offer critical insights into the selection of context-aware algorithms and identify key research gaps, an essential step for advancing the reliability and applicability of AI-driven seagrass conservation efforts.…"
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2
Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle
منشور في 2025"…To evaluate the generalizability of the algorithms, the agents are tested across various velocities, tire–road friction coefficients, and additional scenarios implemented in IPG CarMaker, a high-fidelity vehicle dynamics simulator. …"
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3
DAP: A dataset-agnostic predictor of neural network performance
منشور في 2024"…This task often must be repeated many times, especially when developing a new deep learning algorithm or performing a neural architecture search. …"
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4
PROVOKE: Toxicity trigger detection in conversations from the top 100 subreddits
منشور في 2022"…<p>Promoting healthy discourse on community-based online platforms like Reddit can be challenging, especially when conversations show ominous signs of toxicity. …"
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5
Artificial intelligence-enhanced electrocardiography for accurate diagnosis and management of cardiovascular diseases
منشور في 2024"…However, the ECG can be interpreted differently by humans depending on the interpreter's level of training and experience, which could make diagnosis more difficult. Using AI, especially deep learning convolutional neural networks (CNNs), to look at single, continuous, and intermittent ECG leads that has led to fully automated AI models that can interpret the ECG like a human, possibly more accurately and consistently. …"
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6
Impacts of climate change on the global spread and habitat suitability of <i>Coxiella burnetii</i>: Future projections and public health implications
منشور في 2025"…</p><h3>Materials and methods</h3><p dir="ltr">An ensemble<u> species distribution modelling </u>approach, integrating regression-based and machine-learning algorithms (GLM, GBM, RF, MaxEnt), was used to project habitat suitability (Current time and by 2050, 2070, and 2090). …"