A dual-stage deep learning approach for robust detection and identification of hardware trojans using monte-carlo dropout by Arash Golabi (21841484)

“…This paper presents a dual-path deep learning framework for the detection and identification of HTs via side-channel analysis. …”

Hierarchical deep learning approach using fusion layer for Source Camera Model Identification based on video taken by smartphone by Younes Akbari (16303286)

“…Camera model identification can also help identify the perpetrators or narrow down the search and can be used to enhance SCI systems. In this context, existing approaches such as the Photo Response Non-Uniformity (PRNU) based methods and machine learning techniques such as the support vector machine (SVM) and deep learning models are commonly used solutions. …”

An Ensemble Deep Learning Approach for Accurate Urinary Sediment Detection Using YOLOv9e and KD-YOLOX-ViT by Mansura Naznine (21399893)

“…This study introduces an advanced deep learning method that utilizes ensemble of YOLOv9e and KD-YOLOX-ViT models. …”

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

“…Internet of Things (IoT) and Artificial Intelligence (AI) technologies are currently replacing the traditional methods of handling buildings, infrastructure, and facilities design, control, and maintenance due to their precision and ease of use. 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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Hierarchical deep learning approach using fusion layer for Source Camera Model Identification based on video taken by smartphone by Younes, Akbari

“…Camera model identification can also help identify the perpetrators or narrow down the search and can be used to enhance SCI systems. In this context, existing approaches such as the Photo Response Non-Uniformity (PRNU) based methods and machine learning techniques such as the support vector machine (SVM) and deep learning models are commonly used solutions. …”
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A Novel Deep Learning and Ensemble Learning Mechanism for Delta-Type COVID-19 Detection by Habib Ullah Khan (12024579)

“…To address these issues, the proposed research study presents a hybrid deep learning model for the accurate diagnosing of Delta-type COVID-19 infection using X-ray images. …”

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

Two-Stage Deep Learning Solution for Continuous Arabic Sign Language Recognition Using Word Count Prediction and Motion Images by Shanableh, Tamer

“…As such, two deep learning models are generated; one for predicting the number of words per sentence and the other for recognizing the meaning of the sign language sentences. …”
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Privacy Preservation of Data-Driven Models in Smart Grids Using Homomorphic Encryption by Dabeeruddin Syed (16864260)

“…The results for fault localization show that the classification accuracy of the proposed privacy-preserving deep learning model while using homomorphic encryption is 97–98%, which is close to 98–99% classification accuracy of the model on plain data. …”

Deep Reinforcement Learning for Internet of Drones Networks: Issues and Research Directions by Noor Aboueleneen (17984101)

“…Due to the highly dynamic nature of IoD networks, conventional methods are expected to encounter inadequacies that can be resolved using emerging deep reinforcement learning (DRL) techniques. …”

Design and implementation of a deep learning-empowered m-Health application by Akhan Akbulut (17380285)

“…Later, the web service classifies using the pre-trained model built based on a deep learning algorithm. …”

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. …”

Cloud-based deep learning-assisted system for diagnosis of sports injuries by Xiaoe Wu (17541951)

“…Consequently, this paper proposes a Deep Learning-assisted System (DLS) for diagnosing sports injuries using the Internet of Things (IoT) and the concept of cloud computing. …”

Evaluating Citizens’ Sentiments in Smart Cities: A Deep Learning Approach by Elabora, Abdallah

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A Deep Learning-Based Sensor Modeling for Smart Irrigation System by Maira Sami (19547806)

“…The results of the experiment show that the proposed deep learning-based neural sensor predicts the real-time values with high accuracy, especially the temperature values. …”

Multimodal deep learning for liver cancer applications: a scoping review by Aisha Siam (17293957)

“…</p><h3>Conclusion</h3><p dir="ltr">The use of multimodal data and deep learning techniques can help in the diagnosis and prediction of HCC. …”

Vehicular Environment Identification Based on Channel State Information and Deep Learning by Hadid, Abdenour

“…This paper presents a novel vehicular environment identification approach based on deep learning. It consists of exploiting the vehicular wireless channel characteristics in the form of Channel State Information (CSI) in the receiver side of a connected vehicle in order to identify the environment type in which the vehicle is driving, without any need to implement specific sensors such as cameras or radars. …”
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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)

“…<p>This research work aims to develop a deep learning-based crop classification framework for remotely sensed time series data. …”

The use of multi-task learning in cybersecurity applications: a systematic literature review by Shimaa Ibrahim (22155739)

Artificial Intelligence Chatbots: A Survey of Classical versus Deep Artificial Intelligence Chatbots: A Survey of Classical versus Deep Machine Learning Techniques by A. Alazzam, Bayan

“…In addition to classical ML techniques, Deep Learning (DL) has attracted many researchers to develop chatbots using more sophisticated and accurate techniques. …”
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