A FeedForward–Convolutional Neural Network to Detect Low-Rate DoS in IoT by Harun Surej Ilango (17545728)

“…The existing AI-based detection algorithms in the literature are signature-based, and their efficacy in detecting unknown LR DoS attacks was not explored. …”

Autism Detection of MRI Brain Images Using Hybrid Deep CNN With DM-Resnet Classifier by JAIN, SWETA

“…The hyper parameters are optimized with DM optimization algorithm which improves the accuracy of classifier. …”
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A Novel Fault Diagnosis of Uncertain Systems Based on Interval Gaussian Process Regression: Application to Wind Energy Conversion Systems by Majdi Mansouri (16869885)

“…In the proposed IGPR-RF technique, the effective interval-valued nonlinear statistical features are extracted and selected using the IGPR model and then fed to the RF algorithm for fault classification purposes. …”

Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review by Avneet Kaur (712349)

“…However, AI tools, for instance, Machine Learning (ML) and Deep Learning (DL), offer precise and well-timed solutions for disease detection, classification, and eradication. A comprehensive review of literature has been conducted by examining over 400 articles to focus on 72 studies including 14 reviews publications on ML and DL models about potato disease forecasting using different techniques. …”

Retinal imaging based glaucoma detection using modified pelican optimization based extreme learning machine by Debendra Muduli (20748758)

“…For mass fundus image-based glaucoma classification, an improved automated computer-aided diagnosis (CAD) model performing binary classification (glaucoma or healthy), allowing ophthalmologists to detect glaucoma disease correctly in less computational time. …”

Detecting latent classes in tourism data through response-based unit segmentation (REBUS) in Pls-Sem by Assaker, Guy

“…This research note describes Response-Based Unit Segmentation (REBUS), a “latent class detection” technique used in partial least squares–structural equation modeling (PLS-SEM) to examine data heterogeneity. …”
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MSD-NAS: multi-scale dense neural architecture search for real-time pedestrian lane detection by Sui Paul Ang (18460605)

“…However, they lack practicality for real-time pedestrian lane detection due to non-optimal accuracy, speed, and model size trade-off. …”

Novel Multi Center and Threshold Ternary Pattern Based Method for Disease Detection Method Using Voice by Turker Tuncer (16677966)

“…Smart health systems can be an easy and fast support to voice pathology detection. The identification of an algorithm that discriminates between pathological and healthy voices with more accuracy is needed to obtain a smart and precise mobile health system. …”

A Novel Approach for Detecting Anomalous Energy Consumption Based on Micro-Moments and Deep Neural Networks by Yassine Himeur (14158821)

“…This paper introduces a new solution to detect energy consumption anomalies based on extracting micro-moment features using a rule-based model. …”

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

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Modeling and Guidance of an Underactuated Autonomous Underwater Vehicle by Wadi, Ali H M

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Deep Learning in the Fast Lane: A Survey on Advanced Intrusion Detection Systems for Intelligent Vehicle Networks by Mohammed Almehdhar (22046597)

“…Our systematic review covers a range of AI algorithms, including traditional ML, and advanced neural network models, such as Transformers, illustrating their effectiveness in IDS applications within IVNs. …”

Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network by Mohammad Reza Chalak Qazani (13893261)

“…Computational techniques, like the finite element method, are used to analyse behaviours based on varied input parameters. …”

YOLO-SAIL: Attention-Enhanced YOLOv5 With Optimized Bi-FPN for Ship Target Detection in SAR Images by Prabu Selvam (22330264)

“…The proposed model, YOLO-SAIL, achieves an F1-score of 98.22% in SSDD datasets and 94.68% in HRSID datasets, outperforming most existing models.…”

Malware detection for mobile computing using secure and privacy-preserving machine learning approaches: A comprehensive survey by Faria Nawshin (21841598)

“…As new <u>malware</u> gets introduced frequently by <u>malware developers</u>, it is very challenging to come up with comprehensive algorithms to detect this malware. There are many machine-learning and deep-learning algorithms have been developed by researchers. …”

Diagnostic performance of artificial intelligence in detecting and subtyping pediatric medulloblastoma from histopathological images: A systematic review by Hiba Alzoubi (18001609)

“…</p><h3>Conclusion</h3><p dir="ltr">AI algorithms show promise in detecting and subtyping medulloblastomas, but the findings are limited by overreliance on one dataset, small sample sizes, limited study numbers, and lack of meta-analysis Future research should develop larger, more diverse datasets and explore advanced approaches like deep learning and foundation models. …”

Ensemble-Based Spam Detection in Smart Home IoT Devices Time Series Data Using Machine Learning Techniques by Ameema Zainab (16864263)

“…The obtained results illustrate the efficacy of the proposed algorithm to analyze the time series data from the IoT devices for spam detection.…”

Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval by Mohammed Tahar Habib Kaib (21633176)

“…Generally, RKPCA reduces the number of samples in the training data set and then builds the KPCA model based on this data set. In this paper, the proposed algorithm selects relevant observations from the original data set by utilizing a class interval technique (i.e. histogram) to maintain a bunch of representative samples from each bin. …”

Motion Artifacts Correction From EEG and fNIRS Signals Using Novel Multiresolution Analysis by Md. Shafayet Hossain (16888833)

Bird’s Eye View feature selection for high-dimensional data by Samir Brahim Belhaouari (16855434)

“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”