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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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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Brain tumor detection through image fusion using whale optimization and edge preserving filter by Bhattiprolu Nagasirisha, Venkatesh Munagala, Ramakrishna Reddy Eamani, Mocherla Venkata Srikanth, Asileti Suneel Kumar, Varre Venkata Kanaka Durga Prasad

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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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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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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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Thermonuclear Superburst of MAXI J1752−457 Observed with NinjaSat and MAXI by Amira Aoyama, Teruaki Enoto, Takuya Takahashi, Sota Watanabe, Tomoshi Takeda, Wataru Iwakiri, Kaede Yamasaki, Satoko Iwata, Naoyuki Ota, Arata Jujo, Toru Tamagawa, Tatehiro Mihara, Chin-Ping Hu, Akira Dohi, Nobuya Nishimura, Motoko Serino, Motoki Nakajima, Takao Kitaguchi, Yo Kato, Nobuyuki Kawai, (NinjaSat collaboration)

“…An uncatalogued bright X-ray transient was detected with MAXI on 2024 November 9, named MAXI J1752−457. …”
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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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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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Simple Single-Person Fall Detection Model Using 3D Pose Estimation Mechanisms by Jinmo Yang, R. Young Chul Kim

“…Although various technologies with wearables and vision systems that utilize artificial intelligence (AI) have been developed to detect falls, many AI models are complex and resource-intensive. …”
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Enhanced Intrusion Detection in In-Vehicle Networks Using Advanced Feature Fusion and Stacking-Enriched Learning by Ali Altalbe

“…To address this problem, machine learning (ML) based intrusion detection systems (IDSs) have been proposed. However, existing IDSs suffer from low detection accuracy, limited real-time response, and high resource requirements. …”
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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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Evaluation of a coastal acoustic buoy for cetacean detections, bearing accuracy and exclusion zone monitoring by Kaitlin J. Palmer, Sam Tabbutt, Douglas Gillespie, Jesse Turner, Paul King, Dominic Tollit, Jessica Thompson, Jason Wood

“…Field trials indicated maximum detection ranges from 4–7.3 km depending on source and ambient noise levels. …”
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F-OSFA: A Fog Level Generalizable Solution for Zero-Day DDOS Attacks Detection by Muhammad Rashid Minhas, Qaisar M. Shafi, Shoab Ahmed Khan, Tahir Ahmad, Subhan Ullah, Attaullah Buriro, Muhammad Azfar Yaqub

“…The third component is a signature-based resource usage analyzer to counter attacks mimicking normal traffic. …”
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DNA-Based Nanobiosensor for the Colorimetric Detection of Dengue Virus Serotype 2 Synthetic Target Oligonucleotide by Michael Sandino C. Flores, Evangelyn C. Alocilja, Divina M. Amalin, Mae Joanne B. Aguila, Marynold V. Purificacion, Florinia E. Merca, Ma. Carmina C. Manuel, Mark Pierre S. Dimamay, Ma. Anita M. Bautista, Lilia M. Fernando

“…Being a developing country, most of the high-risk areas in the Philippines are resource-limited and cannot afford equipment for detection and monitoring. …”
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Acoustic Emission as a Method for Analyzing Changes and Detecting Damage in Composite Materials During Loading by Katarzyna PANASIUK, Krzysztof DUDZIK, Grzegorz HAJDUKIEWICZ

“…The signal obtained from the sensor was then further processed and used to draw up diagrams of the AE hits, amplitude, root mean square of the AE source signal (RMS) and duration in the function of time. …”
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Securing Industrial IoT Environments: A Fuzzy Graph Attention Network for Robust Intrusion Detection by Safa Ben Atitallah, Maha Driss, Wadii Boulila, Anis Koubaa

“…The Industrial Internet of Things (IIoT) faces significant cybersecurity threats due to its ever-changing network structures, diverse data sources, and inherent uncertainties, making robust intrusion detection crucial. …”
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LMGD: Log-Metric Combined Microservice Anomaly Detection Through Graph-Based Deep Learning by Xu Liu, Yuewen Liu, Miaomiao Wei, Peng Xu

“…Therefore, there is an urgent need for fast and accurate anomaly detection capabilities. However, the existing microservice anomaly detection methods do not pay attention to the multi-source data of the microservice system and thus have low accuracy. …”
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CSW-YOLO: A traffic sign small target detection algorithm based on YOLOv8. by Qian Shen, Yi Li, YuXiang Zhang, Lei Zhang, ShiHao Liu, Jinhua Wu

“…First, the bottleneck of the C2f module in the original yolov8 network is replaced with the residual Faster-Block module in FasterNet, and then the new channel mixer convolution GLU (CGLU) in TransNeXt is combined with it to construct the C2f-faster-CGLU module, reducing the number of model parameters and computational load; Secondly, the SPPF module is combined with the large separable kernel attention (LSKA) to construct the SPPF-LSKA module, which greatly enhances the feature extraction ability of the model; Then, by adding a small target detection layer, the accuracy of small target detection such as traffic signs is greatly improved; Finally, the Inner-IoU and MPDIoU loss functions are integrated to construct WISE-Inner-MPDIoU, which replaces the original CIoU loss function, thereby improving the calculation accuracy. …”
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