New Algorithms for Deep Learning Machines by unknown

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Leveraging Machine and Deep Learning Algorithms for hERG Blocker Prediction by Syed Mohammad (21075689)

“…The application of machine learning (ML) and deep learning (DL) models in the field of toxicity has gained burgeoning interest. …”

On the performance of fusion based planet-scope and Sentinel-2 data for crop classification using inception inspired deep convolutional neural network by Nasru Minallah (9427338)

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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT by Dhananjay Bisen (19482454)

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Comparative Analysis of Supervised Machine and Deep Learning Algorithms for Kyphosis Disease Detection by Alok Singh Chauhan (8264985)

Classifying Maqams of Qur'anic Recitations Using Deep Learning by Shahriar, Sakib

Subjects: “…Deep learning…”
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Exploring Semi-Supervised Learning Algorithms for Camera Trap Images by Sajun, Ali Reza

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Content-Aware Adaptive Video Streaming Using Actor-Critic Deep Reinforcement Learning by Amer, Hala Nagi

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A systematic review of text classification research based on deep learning models in Arabic language by Wahdan, Ahlam

“…Our results provide some findings regarding how deep learning models can be used to improve text classification research in Arabic language.…”
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Wind, Solar, and Photovoltaic Renewable Energy Systems with and without Energy Storage Optimization: A Survey of Advanced Machine Learning and Deep Learning Techniques by Abu Zitar, Raed

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An Efficient Prediction System for Diabetes Disease Based on Deep Neural Network by Tawfik Beghriche (19563184)

“…In this work, an efficient medical decision system for diabetes prediction based on Deep Neural Network (DNN) is presented. …”

AI and IoT-based concrete column base cover localization and degradation detection algorithm using deep learning techniques by Khalid, Naji

“…This paper proposes a novel automated algorithm for the health monitoring of concrete column base cover degradation based on IoT and the state-of-the-art deep learning framework, Convolutional Neural Network (CNN). …”
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Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches by Natasha Akram (20749538)

“…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …”

Deep learning-based user experience evaluation in distance learning by Rahim Sadigov (17714301)

“…More than 160,000 tweets, addressing conditions related to the major change in the education system, were gathered from Twitter social network and deep learning-based sentiment analysis models and topic models based on latent dirichlet allocation (LDA) algorithm were developed and analyzed. …”

USER ASSOCIATION IN HYBRID VLC/RF CELL-FREE MASSIVE MIMO SYSTEMS VIA ITERATIVE ALGORITHMS AND DEEP REINFORCEMENT LEARNING by unknown

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Automated Deep Learning BLACK-BOX Attack for Multimedia P-BOX Security Assessment by Zakaria Tolba (16904718)

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Navigating the Landscape of Deep Reinforcement Learning for Power System Stability Control: A Review by Mohamed Sadok Massaoudi (17984071)

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A Fusion-Based Approach for Skin Cancer Detection Combining Clinical Images, Dermoscopic Images, and Metadata by Siddiqui, Ansah Juned

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Deep Reinforcement Learning for Resource Constrained HLS Scheduling by Makhoul, Rim

“…In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. The actions and rewards for the proposed algorithm are selected carefully to guide the agent to its objective. …”
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Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization by Yassine Himeur (14158821)

“…While artificial intelligence (AI) smooths the path of computers to think like humans, machine learning (ML) and deep learning (DL) pave the way more, even by adding training and learning components. …”