Underwater image dehazing using a hybrid GAN with bottleneck attention and improved Retinex-based optimization by Amandeep Kaur, Shalli Rani, Mohammad Shabaz

“…This study presents exceptional quantitative performance across various evaluation metrics: a UIQM score of 3.71 (indicating image quality), a PSNR of 28.4 dB (reflecting signal fidelity), an SSIM of 0.88 (representing structural similarity), and a perceptual LPIPS score of 0.082. …”
Get full text

AN INTELLIGENT POSTOPERATIVE CHRONIC PAIN PREDICTION SYSTEM (I-POCPP) by Elif Kartal, Fatma Önay Koçoğlu, Zeki Özen, İlkim Ecem Emre, Gürcan Güngör, Pervin Sutaş Bozkurt

“…Objective: Postoperative Chronic Pain (POCP) affects the quality of patients’ lives. Machine learning and its applications provide significant contributions to pain research. …”
Get full text

Enhancing Accessibility Through Machine Learning: A Review on Visual and Hearing Impairment Technologies by Pal Patel, Shreyansh Pampaniya, Ananya Ghosh, Ritu Raj, Deepa K, Saravanakumar Kandasamy

“…For hearing impairments, the analysis focuses on advanced models such as Support Vector Machines (SVM), Random Forests (RF), and Multi-Layer Perceptrons (MLP), examining their effectiveness in auditory assistive applications. In the context of visual impairments, state-of-the-art object detection frameworks like You Only Look Once (YOLO), Single Shot MultiBox Detector (SSD), and RetinaNet are evaluated for their capability to enable real-time object recognition and navigation aids. …”
Get full text

Assessing Lightweight Folding UAV Reliability Through a Photogrammetric Case Study: Extracting Urban Village’s Buildings Using Object-Based Image Analysis (OBIA) Method by Junyu Kuang, Yingbiao Chen, Zhenxiang Ling, Xianxin Meng, Wentao Chen, Zihao Zheng

“…With the rapid advancement of drone technology, modern drones have achieved high levels of functional integration, alongside structural improvements that include lightweight, compact designs with foldable features, greatly enhancing their flexibility and applicability in photogrammetric applications. Nevertheless, limited research currently explores data collected by such compact UAVs, and whether they can balance a small form factor with high data quality remains uncertain. …”
Get full text

An End-to-End Solution for Large-Scale Multi-UAV Mission Path Planning by Jiazhan Gao, Liruizhi Jia, Minchi Kuang, Heng Shi, Jihong Zhu

“…The MHA module effectively models global spatial-task dependencies among nodes, enhancing solution quality. Additionally, we integrate a Multi-Start Greedy Rollout Baseline to evaluate diverse trajectories via parallelized greedy searches, thereby reducing policy gradient variance and improving training stability. …”
Get full text

Machine Learning‐Enhanced Optimization for High‐Throughput Precision in Cellular Droplet Bioprinting by Jaemyung Shin, Ryan Kang, Kinam Hyun, Zhangkang Li, Hitendra Kumar, Kangsoo Kim, Simon S. Park, Keekyoung Kim

“…In this study, a high‐throughput cellular droplet bioprinter is designed, capable of printing over 50 cellular droplets simultaneously, producing the large dataset required for effective machine learning training. Among the five algorithms evaluated, the multilayer perceptron model demonstrates the highest prediction accuracy, while the decision tree model offers the fastest computation time. …”
Get full text

Classification of single tree decay stages from combined airborne LiDAR data and CIR imagery by Tsz-Chung Wong, Abubakar Sani-Mohammed, Jinhong Wang, Puzuo Wang, Wei Yao, Marco Heurich

“…The monitoring of forest health is, therefore, indispensable for the long-term conservation of forests and their sustainable management. In this regard, evaluating the amount and quality of dead wood is of utmost interest as they are favorable indicators of biodiversity. …”
Get full text

Diagnostic models for sepsis-associated encephalopathy: a comprehensive systematic review and meta-analysis by Tengfei Zhou, Tengfei Zhou, Xinming Tian, Wei Wang, Zhe Chu

“…All models showed a high risk of bias according to the PROBAST evaluation, mainly due to the lack of external validation and methodological shortcomings.ConclusionCurrent SAE prediction models demonstrate moderate discriminatory ability, but their methodological quality remains poor, and they are not yet suitable for routine clinical application. …”
Get full text

AGW-YOLO-Based UAV Remote Sensing Approach for Monitoring Levee Cracks by HU Weibo, ZHOU Shaoliang, ZHAO Erfeng, ZHAO Xueqiang

“…This loss function incorporates an outlier degree evaluation and a dynamic non-monotonic focusing mechanism, which adaptively adjusts the optimization intensity of anchor boxes with varying qualities. …”
Get full text

Multiobjective Design Optimization of Grillage Systems according to LRFD-AISC by Tugrul Talaslioglu

“…Hence, while the computational performances of these four optimization algorithms are compared using different combinations of optimizer-related parameters, the various strengths of grid members are also evaluated. …”
Get full text

Tomografía geoeléctrica: dos ejemplos en la Sabana de Bogotá by Briceno Guarupe Luis Alberto, Sanín Camilo Ernesto

“…This geophysic tool is very useful in shallow applications (100 m depth), and where high resolution and quality are needed.…”
Get full text

Cloud Removal Advances: A Comprehensive Review and Analysis for Optical Remote Sensing Images by Jin Ning, Lianbin Xie, Jie Yin, Yiguang Liu

“…Cloud cover significantly decreases the quality of optical remote sensing (ORS) images, adversely impacting its effectiveness in geographic monitoring, disaster prevention, and advanced visual applications. …”
Get full text

Ultrasound-based machine learning model to predict the risk of endometrial cancer among postmenopausal women by Yi-Xin Li, Yu Lu, Zhe-Ming Song, Yu-Ting Shen, Wen Lu, Min Ren

“…Abstract Background Current ultrasound-based screening for endometrial cancer (EC) primarily relies on endometrial thickness (ET) and morphological evaluation, which suffer from low specificity and high interobserver variability. …”
Get full text

TSHD: Topic Segmentation Based on Headings Detection (Case Study: Resumes) by Majd E. Tannous, Wassim H. Ramadan, Mohanad A. Rajab

“…This can improve the quality of many NLP applications such as information extraction, information retrieval, summarization, and question answering. …”
Get full text

Comparative analysis of image mosaicing techniques for aerial agriculture field imaging by Maria John, S. Santhanalakshmi, J Amudha, Jianfeng Zhou

“…The objective of this work is to evaluate and compare image mosaicing techniques, focusing primarily on agricultural datasets. …”
Get full text

Digital image representation by atomic functions: features for computer vision and machine learning by Viktor Makarichev, Vladimir Lukin, Sergii Kryvenko, Iryna Brysina

“…We evaluated the performance of the well-known k-means clustering algorithm when applied to DAT images. …”
Get full text

Opportunistic Diagnostics of Dental Implants in Routine Clinical Photon-Counting CT Acquisitions by Maurice Ruetters, Holger Gehrig, Christian Mertens, Sinan Sen, Ti-Sun Kim, Heinz-Peter Schlemmer, Christian H. Ziener, Stefan Schoenberg, Matthias Froelich, Marc Kachelrieß, Stefan Sawall

“…Conventional CT scans, such as those of the cervical spine, have so far lacked the resolution to reliably evaluate dental structures or implants. This study evaluates the diagnostic utility of PCCT for visualizing peri-implant structures in routine clinical photon-counting CT acquisitions and assesses the influence of metal artifact reduction (MAR) algorithms on image quality. …”
Get full text

Artificial intelligence-assisted capsule endoscopy for detecting lesions in Crohn’s disease: a systematic review and meta-analysis by Yuling Bin, Rumei Peng, Yaqian Lee, Zhijie Lee, Yang Liu

“…However, given the limitations and heterogeneity of current research, more high-quality, large-sample studies are needed to comprehensively and thoroughly evaluate the practical application value of AI in CD diagnosis, thereby promoting its widespread adoption and optimization in clinical practice.…”
Get full text

Raman Spectra Classification of Pharmaceutical Compounds: A Benchmark of Machine Learning Models with SHAP-Based Explainability by Dimitris Kalatzis, Alkmini Nega, Yiannis Kiouvrekis

“…A diverse array of algorithms—including Support Vector Machines (SVMs), Random Forests, k-Nearest Neighbors (k-NN), Gradient Boosting (XGBoost, LightGBM), and 1D Convolutional Neural Networks (CNNs)—were evaluated on a publicly available dataset. …”
Get full text

Vehicular-Computational Resource Geofencing: Efficient Spatiotemporal Uncertainty Estimation by Ghada Afifi, Bassem Mokhtar

“…However, existing VCC solutions are unable to satisfy the stringent quality of experience (QoE) requirements for running vehicular applications, especially delay- and throughput-sensitive applications, given the high communication delay and latency with the central cloud. …”
Get full text