Deterministic Light Detection and Ranging (LiDAR)-Based Obstacle Detection in Railways Using Data Fusion by Susana Dias, Pedro J. S. C. P. Sousa, João Nunes, Francisco Afonso, Nuno Viriato, Paulo J. Tavares, Pedro M. G. P. Moreira

“…Therefore, the timely detection of obstacles is crucial for ensuring operational safety. …”
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Eye Detection using Helmholtz Principle by Ahmed et al.

“…Eye Detection is used in many applications like pattern recognition, biometric, surveillance system and many other systems. …”
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Effects of anlotinib hydrochloride on the expression of immunogenic cell death-related molecules in Cal27 tongue cancer cells by Pengcheng Huang, Jitao Zhu, Lijuan Guo, Zong Yao Zhang, Li Guan, Sen Yang

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A Comparative Study of Image Processing and Machine Learning Methods for Classification of Rail Welding Defects by Mohale Emmanuel Molefe, Jules Raymond Tapamo, Siboniso Sithembiso Vilakazi

“…A comparative investigation is carried out between Deep Convolution Neural Networks, Local Binary Pattern extractors, and Bag of Visual Words methods (with the Speeded-Up Robust Features extractor) for extracting features in weld joint images. …”
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Morphological functional criteria of neuroprotective therapy efficacy in glaucomatous optic neuropathy by Tszin Dan

“…Electrophysiological tests may be used to detect early glaucomatous changes and glaucoma progression risk and to monitor treatment efficacy. …”
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Statistical voxel-wise analysis of ictal SPECT reveals pattern of abnormal perfusion in patients with temporal lobe epilepsy Análise estatística baseada em voxel do SPECT ictal rev... by Bárbara Juarez Amorim, Elba Cristina Sá de Camargo Etchebehere, Edwaldo Eduardo Camargo, Pablo Augusto Rio, Leonardo Bonilha, Chris Rorden, Li Min Li, Fernando Cendes

“…OBJECTIVE: To investigate the pattern of perfusion abnormalities in ictal and interictal brain perfusion SPECT images (BSI) from patients with temporal lobe epilepsy (TLE). …”
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Detection of asynchronicity in the amplitude modulation domain by D. Kutzner, J. Lemańska, A. P. Sęk

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Detecting change in stochastic sound sequences. by Benjamin Skerritt-Davis, Mounya Elhilali

“…Previous work in regularity extraction has predominantly focused on the brain's sensitivity to predictable patterns in sound sequences. However, natural sound environments are rarely completely predictable, often containing some level of randomness, yet the brain is able to effectively interpret its surroundings by extracting useful information from stochastic sounds. …”
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An Algorithm to Automatically Detect the Smale Horseshoes by Qingdu Li, Lina Zhang, Fangyan Yang

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Distributed Abnormal Activity Detection in Smart Environments by Chengliang Wang, Qian Zheng, Yayun Peng, Debraj De, Wen-Zhan Song

“…DetectingAct works as follows. Firstly, DetectingAct finds the normal activity patterns through duration-dependent frequent pattern mining algorithm (DFPMA), which adopts unsupervised learning instead of supervised learning. …”
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An embedded intelligence engine for driver drowsiness detection by Shirisha Vadlamudi, Ali Ahmadinia

“…Drowsiness of drivers was detected based on steering wheel movement and lane change patterns. …”
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K-Complex Detection Based on Synchrosqueezing Transform by Z. Ghanbari, M. H. Moradi

“…K-complex is an underlying pattern in the sleep EEG. Due to the role of sleep studies inneurophysiologic and cognitive disorders diagnosis, reliable methods for analysis and detection of this patternare of great importance. …”
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The New Paradigm of Deepfake Detection at the Text Level by Cosmina-Mihaela Rosca, Adrian Stancu, Emilian Marian Iovanovici

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BERT-based network for intrusion detection system by Yong Yang, Xing Peng

“…Abstract The rising complexity of cyberattacks poses significant challenges to traditional intrusion detection system (IDS). Approaches that rely mainly on feature engineering and rule matching often fail to address new and complex attack patterns effectively. …”
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Detection of venous thromboembolism by proteomic serum biomarkers. by Santhi K Ganesh, Yugal Sharma, Judith Dayhoff, Henry M Fales, Jennifer Van Eyk, Thomas S Kickler, Eric M Billings, Elizabeth G Nabel

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On the Kinematics of Vehicles Relevant to Conflict Detection and Resolution by Luís Braga Campos, Joaquim Guerreiro Marques

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Incremental Adversarial Learning for Polymorphic Attack Detection by Ulya Sabeel, Shahram Shah Heydari, Khalil El-Khatib, Khalid Elgazzar

“…The results indicate that the proposed technique, through adaptive training, learns the pattern of dynamically changing atypical/polymorphic attacks, identifies such attacks with approximately 90% balanced accuracy for most of the cases, and surpasses various state-of-the-art detection and class balancing techniques.…”
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Enhanced Multi-Class Detection of Fake News by Chih-yuan Li, Soon Ae Chun, James Geller

“…Our experiment demonstrates CNN's effectiveness in identifying text patterns. To address class imbalances, we experimented with three different balancing methods. …”
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Uncertainty-Aware Time Series Anomaly Detection by Paul Wiessner, Grigor Bezirganyan, Sana Sellami, Richard Chbeir, Hans-Joachim Bungartz

“…However, consideration of noise in data is important as it may have the potential to lead to more robust detection of anomalies and a better capability of distinguishing between real anomalies and anomalous patterns provoked by noise. …”
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Self-Supervised Autoencoders for Visual Anomaly Detection by Alexander Bauer, Shinichi Nakajima, Klaus-Robert Müller

“…We focus on detecting anomalies in images where the data distribution is supported by a lower-dimensional embedded manifold. …”
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