GastroEndoNet: Comprehensive endoscopy image dataset for GERD and polyp detectionMendeley Data by Abu Kowshir Bitto, Md. Hasan Imam Bijoy, Kamrul Hassan Shakil, Aka Das, Khalid Been Badruzzaman Biplob, Imran Mahmud, Syed Md. Minhaz Hossain

“…It provides an invaluable resource for developing machine learning models aimed at the automatic diagnosis, classification, and detection of GERD and polyps, potentially improving the speed and accuracy of clinical decision-making. …”
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From fish to fiber: 3D-nanoprinted optical neuromast for multi-integrated underwater detection by Liangye Li, Xuhao Fan, Geng Chen, Yueqi Liu, Fujun Zhang, Zhuolin Chen, Zhi Zhang, Wangyang Xu, Shixiong Zhang, Yuncheng Liu, Zongjing Li, Hui Gao, Zhijun Yan, Wei Xiong, Qizhen Sun

“…Abstract Fish possess high sensitivity to acoustic, vibrational, and hydrodynamic stimuli through unique sensing cells, providing unparalleled paradigms for developing underwater detection methods. However, artificial perception devices face challenges in replicating comparable sensitivity and multi-dimensional integration of fish in function and scale. …”
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Improved detection of decreased glucose handling capacities via continuous glucose monitoring-derived indices by Hikaru Sugimoto, Ken-ichi Hironaka, Tomoaki Nakamura, Tomoko Yamada, Hiroshi Miura, Natsu Otowa-Suematsu, Masashi Fujii, Yushi Hirota, Kazuhiko Sakaguchi, Wataru Ogawa, Shinya Kuroda

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SHIVA-CMB: a deep-learning-based robust cerebral microbleed segmentation tool trained on multi-source T2*GRE- and susceptibility-weighted MRI by Ami Tsuchida, Martin Goubet, Philippe Boutinaud, Iana Astafeva, Victor Nozais, Pierre-Yves Hervé, Thomas Tourdias, Stéphanie Debette, Marc Joliot

“…An increasing number of automated CMB detection methods being proposed are based on supervised deep learning (DL). …”
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Detecting Vegetation Stress in Mixed Forest Ecosystems Through the Joint Use of Tree‐Water Monitoring and Land Surface Modeling by C. D. Jiménez‐Rodríguez, G. Fabiani, R. Schoppach, K. Mallick, S. J. Schymanski, M. Sulis

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Enhancing Human Detection in Occlusion-Heavy Disaster Scenarios: A Visibility-Enhanced DINO (VE-DINO) Model with Reassembled Occlusion Dataset by Zi-An Zhao, Shidan Wang, Min-Xin Chen, Ye-Jiao Mao, Andy Chi-Ho Chan, Derek Ka-Hei Lai, Duo Wai-Chi Wong, James Chung-Wai Cheung

“…VE-DINO enhances detection accuracy by incorporating body part key point information and employing a specialized loss function. …”
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Dual Function Radar and Communication Waveform Design Based on Sub-pulse Hybrid Modulation by Yu LIU, Junhao ZHANG, Xue YAO, Xianxiang YU, Guolong CUI

“…To address the low data rate issue in the design of Dual-Function Radar-Communication (DFRC) waveforms with radar detection as the primary function, this paper proposes an information modulation method for multiple sub-pulse structure waveforms called Sub-pulse Hybrid Modulation (SHM). …”
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Lightweight coal miners and manned vehicles detection model based on deep learning and model compression techniques: A case study of coal mines in Guizhou region by Beijing XIE, Heng LI, Zheng LUAN, Zhen LEI, Xiaoxu LI, Zhuo LI

“…Compared to various lightweight architectures and advanced detection models, this method demonstrates excellent accuracy, lower computational costs, and better real-time performance, providing a feasible coal mine pedestrian-vehicle detection method for resource-constrained coal mine scenarios, meeting the deployment requirements of coal mine video surveillance and enabling real-time alerts for intelligent inspection of coal mine pedestrian-vehicles.…”
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Finite mixtures of functional graphical models: Uncovering heterogeneous dependencies in high-dimensional data. by Qihai Liu, Kevin H Lee, Hyun Bin Kang

“…In this work, we propose finite mixtures of functional graphical models (MFGM), which detect the heterogeneous subgroups of the population and estimate single graph for each subgroup by considering the correlation structures. …”
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Source Process Estimation for the 2024 Mw 7.1 Hyuganada, Japan, Earthquake and Forward Modeling Using N‐net Ocean Bottom Seismometer Data by R. Shibata, H. Kubo, W. Suzuki, S. Aoi, H. Sekiguchi

“…The N‐net seafloor seismograms of the mainshock with a frequency of ∼0.05 Hz recorded east of the source area were reproduced for several stations using the empirical Green's function approach based on the estimated source process data.…”
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STATISTICAL DATA AND ANALYSIS OF LITERATURE SOURCES ON PATHOPHYSIOLOGICAL MECHANISMS OF THE CROSSTALK BETWEEN ACUTE KIDNEY AND LIVER INJURY IN PRETERM NEWBORNS DURING THE EARLY NEO... by О. Оболонська, Л. Вакуленко

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Multimodal imaging analysis and structure-function correlation in patients exposed to pentosan polysulfate sodium by Sandra Hoyek, Eleni Konstantinou, Francesco Romano, Darren Chen, Celine Chaaya, Magdalena G. Krzystolik, Daniel Hu, Rachel Huckfeldt, Demetrios G. Vavvas, Leo A. Kim, Jason Lee, Elise De, John B. Miller, Nimesh A. Patel

“…Purpose: To study the anatomic and functional retinal changes in patients exposed to pentosan polysulfate (PPS) using multimodal imaging and mesopic microperimetry. …”
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Identification and functional analysis of novel precursor genes in cyclic peptide biosynthesis in Pseudostellaria heterophylla by Jiao Xu, Wei Zheng, Xiaohong Ou, Hua He, Changgui Yang, Lanping Guo, Chenghong Xiao, Weike Jiang, Guoping Shu, Tao Zhou

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Detection of VOCs and Biogenic Amines Through Luminescent Zn–Salen Complex-Tethered Pyrenyl Arms by Roberta Puglisi, Caterina Testa, Sara Scuderi, Valentina Greco, Giuseppe Trusso Sfrazzetto, Manuel Petroselli, Andrea Pappalardo

“…Fluorescence titrations and density functional theory (DFT) calculations reveal and explain the high binding affinity of this receptor toward selected amines, demonstrating its potential as an effective tool for amine detection.…”
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Rice-SVBDete: a detection algorithm for small vascular bundles in rice stem’s cross-sections by Xiaoying Zhu, Weiyu Zhou, Jianguo Li, Jianguo Li, Mingchong Yang, Mingchong Yang, Haiyu Zhou, Haiyu Zhou, Jiada Huang, Jiada Huang, Jiahua Shi, Jun Shen, Guangyao Pang, Lingqiang Wang, Lingqiang Wang, Lingqiang Wang

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Relationships between vegetation indices and surface reflectance: Implications for detecting and monitoring sandification in arid regions by Yifan Yue, Wenzhi Zhao, Rentao Liu

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DECISION TREE WITH HILL CLIMBING ALGORITHM BASED SPECTRUM HOLE DETECTION IN COGNITIVE RADIO NETWORK by N Suganthi, R Meenakshi, A Sairam, M Parvathi

“…The approach integrates a Decision Tree (DT) algorithm for rapid initial classification of Primary User (PU) activity, followed by a Hill Climbing (HC) optimization algorithm that fine-tunes the detection based on a fitness function. Entropy and throughput metrics are employed as decision conditions at each sensing channel, enhancing uncertainty measurement and maintaining detection robustness under low Signal-to-Noise Ratio (SNR) conditions. …”
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TCE-YOLOv5: Lightweight Automatic Driving Object Detection Algorithm Based on YOLOv5 by Han Wang, Zhenwei Yang, Qiaoshou Liu, Qiang Zhang, Honggang Wang

“…Finally, the EIOU loss function is introduced to measure the overlap between the predicted box and the real box more accurately and improve the detection accuracy. …”
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DSFA-SwinNet: A Multi-Scale Attention Fusion Network for Photovoltaic Areas Detection by Shaofu Lin, Yang Yang, Xiliang Liu, Li Tian

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YOLOv8n-DDSW: an efficient fish target detection network for dense underwater scenes by Jinwang Yi, Wei Han, Fangfei Lai

“…Therefore, the YOLOv8n-DDSW fish target detection algorithm was proposed in this article to resolve the detection difficulties resulting from fish occlusion, deformation and detail loss in complex intensive aquaculture scenarios. (1) The C2f-deformable convolutional network (DCN) module is proposed to take the place of the C2f module in the YOLOv8n backbone to raise the detection accuracy of irregular fish targets. (2) The dual-pooling squeeze-and-excitation (DPSE) attention mechanism is put forward and integrated into the YOLOv8n neck network to reinforce the features of the visible parts of the occluded fish target. (3) Small detection is introduced to make the network more capable of sensing small targets and improving recall. (4) Wise intersection over union (IOU) rather than the original loss function is used for improving the bounding box regression performance of the network. …”
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