Advanced image preprocessing and context-aware spatial decomposition for enhanced breast cancer segmentation by G. Kalpana, N. Deepa, D. Dhinakaran

“…Furthermore, the use of the improved preprocessing pipeline benefits classification models with improved Convolutional Neural Networks having a classification accuracy of 85.3 % coupled with AUC-ROC of 0.90 which shows a significant enhancement from conventional techniques. • Enhanced segmentation accuracy with advanced preprocessing and CASDN, achieving superior performance metrics. • Robust multi-modality compatibility, ensuring effectiveness across mammograms, ultrasounds, and MRI scans.…”
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TFCNet: A Hybrid Architecture for Multi-Task Restoration of Complex Underwater Optical Images by Shengya Zhao, Xiufen Ye, Xinkui Mei, Shuxiang Guo, Haibin Qi

“…Motivated by the global modeling capability of the Transformer, this paper introduces TFCNet, a complex hybrid-architecture network designed for underwater optical image enhancement and restoration. …”
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Research on Improved Bridge Surface Disease Detection Algorithm Based on YOLOv7-Tiny-DBB by Haichao An, Ying Fan, Zhuobin Jiao, Meiqin Liu

“…The ablation experiments, along with the performance comparison of different network models and visual effect assessments further corroborate the effectiveness of the proposed improvements, providing critical technical support for the deployment of real-time detection systems for bridge surface diseases on industrial edge devices.…”
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Pansharpening via Multiscale Embedding and Dual Attention Transformers by Wensheng Fan, Fan Liu, Jingzhi Li

“…However, long-range and local dependencies modeling and multiscale feature learning are all essential to the pansharpening task. …”
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Elevation-Aware Domain Adaptation for Sematic Segmentation of Aerial Images by Zihao Sun, Peng Guo, Zehui Li, Xiuwan Chen, Xinbo Liu

“…EADA employs a shared encoder and task-specific decoders, enhanced by a spatial attention-based feature fusion module. Experiments on Potsdam and Vaihingen datasets under cross-domain settings (e.g., Potsdam IRRG → Vaihingen IRRG) show that EADA achieves state-of-the-art performance, with a mean IoU of 54.62% and an F1-score of 65.47%, outperforming single-stage baselines. …”
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Brain-Shapelet: A Framework for Capturing Instantaneous Abnormalities in Brain Activity for Autism Spectrum Disorder Diagnosis by Yijie Ren, Zhengwang Xia, Yudong Zhang, Zhuqing Jiao

“…Specially, we develop a feature selection strategy to reduce redundancy in Shapelets and optimize classification performance. …”
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CylinDeRS: A Benchmark Visual Dataset for Robust Gas Cylinder Detection and Attribute Classification in Real-World Scenes by Klearchos Stavrothanasopoulos, Konstantinos Gkountakos, Konstantinos Ioannidis, Theodora Tsikrika, Stefanos Vrochidis, Ioannis Kompatsiaris

“…Extensive experiments using state-of-the-art (SotA) models are reported to validate the dataset’s significance and application prospects, providing baselines for further performance evaluation and in-depth analysis. …”
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A software pipeline for systematizing machine learning of speech data by Jimuel Celeste, Mashrura Tasnim, Amable J. Valdés Cuervo, Enrique A. de la Cal, Eleni Stroulia

“…The machine-learning community has a long-established practice of sharing data sets so that researchers can report the performance of their models on the same data. In the area of speech analysis, and more specifically speech of individuals with mental health and neurocognitive conditions, a number of such data sets exist and are the subject of organized “challenge tasks”. …”
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Development and validation of risk stratification and shared decision-making tool for catheter ablation for atrial fibrillation in patients with heart failure: a multicentre cohort... by Xiaodong Peng, Liu He, Jue Wang, Nan Li, Jing Cui, Shijun Xia, Song Zuo, Chao Jiang, Jinzhu Hu, Kui Hong, Zhuheng Li, Peng Zhang, Ning Zhou, Caihua Sang, Deyong Long, Xin Du, Jianzeng Dong, Changsheng Ma

“…External validation was performed using diverse ethnic populations from the international, multicenter, randomized, open-label CABANA trial. …”
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A multitasking ant system for multi-depot pick-up and delivery location routing problem with time window by Haoyuan Lv, Ruochen Liu, Jianxia Li

“…Existing works related to MDPDLRPTW focus on obtaining a depot location scheme by clustering and perform route planning on it through single-task optimization. …”
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Evaluating the Nuclear Reaction Optimization (NRO) Algorithm for Gene Selection in Cancer Classification by Shahad Alkamli, Hala Alshamlan

“…<b>Conclusions</b>: The study concludes that NRO is a promising gene selection approach, particularly effective in certain datasets, and suggests that future work should explore hybrid models and feature reduction techniques to further enhance its accuracy and efficiency.…”
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Benchmarking of Anomaly Detection Methods for Industry 4.0: Evaluation, Ranking, and Practical Recommendations by Aurélie Cools, Mohammed Amin Belarbi, Sidi Ahmed Mahmoudi

“…We conduct a unified comparison of ten anomaly detection methods, categorizing them according to their reliance on synthetic anomaly generation and their detection strategy, either reconstruction-based or feature-based. All models are trained exclusively on normal data to mirror realistic industrial conditions. …”
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The Impact of Three Specific Collaborative Merging Strategies on Traffic Flow by Xue-Cheng Shang, Feng Liu, Xin-Gang Li, Davy Janssens, Geert Wets

“…Due to the lane-changing behavior, the system with a two-lane main road has more advantages than that featured with a one-lane road, making the former system performing better than the latter under the same strategies; (3) the vehicles on the ramp and main road affect each other, and as the vehicle entering probabilities become large, the traffic flow rate on the main road decreases whereas that on the ramp increases. …”
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Theoretical foundations for intensifying onion set harvesting by A. S. Dorokhov, A. G. Aksenov, A. V. Sibirev, A. G. Ponomarev, N. V. Sazonov

“…It substantiates the functional diagram of a digging-type onion harvester featuring an ultrasonic cleaning module, taking into account the functions of the state, external and control actions, as well as performance indicators. …”
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BEV-CAM3D: A Unified Bird’s-Eye View Architecture for Autonomous Driving with Monocular Cameras and 3D Point Clouds by Daniel Ayo Oladele, Elisha Didam Markus, Adnan M. Abu-Mahfouz

“…Three-dimensional (3D) visual perception is pivotal for understanding surrounding environments in applications such as autonomous driving and mobile robotics. While LiDAR-based models dominate due to accurate depth sensing, their cost and sparse outputs have driven interest in camera-based systems. …”
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SCITUNA: single-cell data integration tool using network alignment by Aissa Houdjedj, Yacine Marouf, Mekan Myradov, Süleyman Onur Doğan, Burak Onur Erten, Oznur Tastan, Cesim Erten, Hilal Kazan

“…Such integration enhances cellular feature identification by leveraging larger data volumes. …”
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An AI assistant for critically assessing and synthesizing clusters of journal articles by Louis Anthony Cox, Jr.

“…Current large language models (LLMs) face significant challenges in attempting to synthesize and critically assess conflicting causal claims in scientific literature about exposure-associated health effects. …”
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Dual-Stream Contrastive Latent Learning Generative Adversarial Network for Brain Image Synthesis and Tumor Classification by Junaid Zafar, Vincent Koc, Haroon Zafar

“…The dual-stream generator in our architecture incorporates two specialized processing pathways: one is dedicated to local feature variation modeling, while the other captures global structural transformations, ensuring a more comprehensive synthesis of medical images. …”
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Deep Learning Innovations for Underwater Waste Detection: An In-Depth Analysis by Jaskaran Singh Walia, Kavietha Haridass, L. K. Pavithra

“…Our results demonstrate that YOLO-based models achieve faster &#x0026; accurate performance, with YOLOv8n and YOLOv7 reaching a detection accuracy of 96%, compared to 81% and 83% for Faster R-CNN and Mask R-CNN, respectively. …”
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Explainable AI reveals tissue pathology and psychosocial drivers of opioid prescription for non-specific chronic low back pain by Michelle W. Tong, Katharina Ziegeler, Virginie Kreutzinger, Sharmila Majumdar

“…These findings demonstrate the potential of multi-modal EMR data and interpretable models to guide more personalized, equitable ns-cLBP management and opioid prescriptions.…”
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