Deep Learning and Recurrence Information Analysis for the Automatic Detection of Obstructive Sleep Apnea by Daniele Padovano, Arturo Martinez-Rodrigo, José M. Pastor, José J. Rieta, Raul Alcaraz

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Advancing plant leaf disease detection integrating machine learning and deep learning by R. Sujatha, Sushil Krishnan, Jyotir Moy Chatterjee, Amir H. Gandomi

“…To capture complex illness patterns, convolutional neural networks (CNNs) such as VGG19 and Inception v3 are utilized. …”
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Self-Supervised Image Anomaly Detection Through Diverse Pseudo Anomaly Insertion by Rizwan Ali Shah, Odilbek Urmonov, Hyungwon Kim

“…Industrial anomaly detection through deep learning-based vision systems is becoming a critical inspection tool for deploying efficient, defect-free manufacturing lines in smart factories. …”
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Enhancing Network Security: A Study on Classification Models for Intrusion Detection Systems by Abeer Abd Alhameed Mahmood, Azhar A. Hadi, Wasan Hashim Al-Masoody

“…The authors utilize three datasets (Knowledge Discovery in Databases 1999 dataset, used for network intrusion detection research), UNSW-NB15 (a dataset capturing contemporary network attack patterns generated at the University of New South Wales), and CICIDS2017 (Canadian Institute for Cybersecurity Intrusion Detection System dataset, containing modern attack scenarios)(KDD99, UNSW NB15, and CICIDS2017) with varying train-test ratios to train the classifiers. …”
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Real‐time object detection for unmanned vehicles in Bangladesh: Dataset, implementation and evaluation by Muhammad Liakat Ali, Topu Biswas, Shahin Akter, Mohammed Farhan Jawad, Hadaate Ullah

“…However, the intelligent identification of road vehicles in a densely populated country like Bangladesh is challenging due to irregular traffic patterns, highly diverse vehicle types, a cluttered environment, and a lack of high‐quality datasets. …”
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An Image-Free Single-Pixel Detection System for Adaptive Multi-Target Tracking by Yicheng Peng, Jianing Yang, Yuhao Feng, Shijie Yu, Fei Xing, Ting Sun

“…Furthermore, the output values of the system are used to continuously update the weight parameters, enabling adaptation to varying motion patterns and ensuring consistent tracking stability. …”
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The Role of AI in Cardiovascular Event Monitoring and Early Detection: Scoping Literature Review by Luis B Elvas, Ana Almeida, Joao C Ferreira

“…The increasing availability of medical data, coupled with AI advancements, offers new opportunities for early detection and intervention in cardiovascular events, leveraging AI’s capacity to analyze complex datasets and uncover critical patterns. …”
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Crypto-Ransomware Detection Through a Honeyfile-Based Approach with R-Locker by Xiang Fang, Eric Song, Cheng Ning, Huseyn Huseynov, Tarek Saadawi

“…By analyzing the recorded parameters after recovery and logging any adverse effects, we were able to train the system for better detection patterns. The proposed solution allows for detection and intervention against the crypto and locker types of ransomware attacks. …”
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INTEGRATED CYBERSECURITY FRAMEWORK FOR ENHANCED THREAT DETECTION AND INCIDENT RESPONSE IN THE DIGITAL ERA by Azlin Ramli, Mohamad Yusof Darus, Yusnani Mohd Yussoff, Badri Azni, Kanqi Xie

“…The advanced threat detection element utilizes AI-driven analytics to spot anomalous patterns and forecast potential vulnerabilities, thus enhancing threat visibility. …”

EEG-Based Emotion Detection Using Roberts Similarity and PSO Feature Selection by Mustafa Hussein Mohammed, Mustafa Noaman Kadhim, Dhiah Al-Shammary, Ayman Ibaida

“…In this paper, a novel classifier based on Robert’s similarity measure is introduced for emotion detection using electroencephalogram (EEG) signals. …”
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Lightweight hybrid transformers-based dyslexia detection using cross-modality data by Abdul Rahaman Wahab Sait, Yazeed Alkhurayyif

“…Traditional dyslexia detection (DD) relies on lengthy, subjective, restricted behavioral evaluations and interviews. …”
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Optimization and validation of echo times of point-resolved spectroscopy for cystathionine detection in gliomas by Min Zhou, Zhuang Nie, Jie Zhao, Yao Xiao, Xiaohua Hong, Yuhui Wang, Chengjun Dong, Alexander P. Lin, Ziqiao Lei

“…Results The TE of PRESS was optimized as (TE1, TE2) = (17 ms, 28 ms). The spectral pattern of cystathionine and aspartate were consistent between calculation and phantom. …”
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Vision transformer embedded video anomaly detection using attention driven recurrence by Ummay Maria Muna, Shanta Biswas, Syed Abu Ammar Muhammad Zarif, Philip Jefferson Deori, Tauseef Tajwar, Swakkhar Shatabda

“…Automated video anomaly detection (VAD) is a challenging task due to its context-dependent and sporadic nature. …”
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PBVit: A Patch-Based Vision Transformer for Enhanced Brain Tumor Detection by Pratikkumar Chauhan, Munindra Lunagaria, Deepak Kumar Verma, Krunal Vaghela, Ghanshyam G. Tejani, Sunil Kumar Sharma, Ahmad Raza Khan

“…These image patches are linearly projected into lower-dimensional token embeddings, and positional encodings are added to help the model understand spatial relationships within the image. PBVit enhances the detection of intricate patterns and anomalies in brain scans, improving diagnostic accuracy. …”
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A systematic review of deep learning methods for community detection in social networks by Mohamed El-Moussaoui, Mohamed Hanine, Ali Kartit, Monica Garcia Villar, Monica Garcia Villar, Monica Garcia Villar, Helena Garay, Helena Garay, Helena Garay, Isabel de la Torre Díez

“…Deep learning has emerged as an effective approach, offering robust capabilities to process large datasets, and uncover intricate relationships and patterns.MethodsIn this systematic literature review, we explore research conducted over the past decade, focusing on the use of deep learning techniques for community detection in social networks. …”
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GeNIS: A modular dataset for network intrusion detection and classificationZenodo by Miguel Silva, Daniela Pinto, João Vitorino, José Gonçalves, Eva Maia, Isabel Praça

“…The development of artificial intelligence solutions for cyberattack detection and classification require high-quality and representative data. …”
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Detection and interpretation of the time-varying seasonal signals in China with multi-geodetic measurements by Liansheng Deng, Yugang Xiao, Qusen Chen, Wei Peng, Zhao Li, Hua Chen, Zhiwen Wu

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Accounting for imperfect detection when estimating species‐area relationships and beta‐diversity by Ciar D. Noble, Carlos A. Peres, James J. Gilroy

“…Abstract Ecologists have historically quantified fundamental biodiversity patterns, including species‐area relationships (SARs) and beta diversity, using observed species counts. …”
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Automotive DNN-Based Object Detection in the Presence of Lens Obstruction and Video Compression by Gabriele Baris, Boda Li, Pak Hung Chan, Carlo Alberto Avizzano, Valentina Donzella

“…The presented parametric obstruction noise model is generated to emulate real-world patterns, whereas compression is based on the well-established AVC/H.264. …”
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Adaptive Defense: Zero-Day Attack Detection in NIDS With Deep Reinforcement Learning by Khorshed Alam, Md Fahad Monir, Md Junayed Hossain, Mohammad Shorif Uddin, Md. Tarek Habib

“…Zero-Day attack detection in Network Intrusion Detection Systems (NIDS) refers to the ability to identify previously unseen attack patterns during testing without having been explicitly trained on those specific attacks, utilizing learned features from other known attacks. …”
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