Enhancing Fake Review Detection Using Linguistic Exaggeration, BERT Embeddings, and Fuzzy Logic by Mohammed Ennaouri, Ahmed Zellou

“…However, the presence of fake reviews threatens the credibility of review platforms, which requires advanced detection mechanisms. The core objective of this work is to develop a hybrid model that combines interpretable handcrafted linguistic cues with deep semantic features for more accurate, robust, and accurate fake review detection. …”
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Value of the 6 min walk test in detecting cardiopulmonary involvement in patients with systemic sclerosis by Sytske Anne Bergstra, Oliver Distler, Cosimo Bruni, Jeska De Vries-Bouwstra, Tom WJ Huizinga, Suzana Jordan, Saad Ahmed, Jacopo Ciaffi, Maarten Ninaber, Sophie I E Liem, Eva M Hoekstra, A A Schouffoer, D Ueckert, Hubert Vliegen

“…The 6 min walk test (6MWT) is widely used to assess functional capacity, but its ability to detect incident CPI remains uncertain. …”
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Accuracy of radiologists and radiology residents in detection of paediatric appendicular fractures with and without artificial intelligence by Timothy Shao Ern Tan, Praveen M Yogendra, Adriel Guang Wei Goh, Sze Ying Yee, Freda Jawan, Kelvin Kay Nguan Koh, Tian Kai Woon, Phey Ming Yeap, Min On Tan

“…Objectives We aim to evaluate the accuracy of radiologists and radiology residents in the detection of paediatric appendicular fractures with and without the help of a commercially available fracture detection artificial intelligence (AI) solution in the hopes of showing potential clinical benefits in a general hospital setting.Methods This was a retrospective study involving three associate consultants (AC) and three senior residents (SR) in radiology, who acted as readers. …”
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An Improved Unmanned Aerial Vehicle Forest Fire Detection Model Based on YOLOv8 by Bensheng Yun, Xiaohan Xu, Jie Zeng, Zhenyu Lin, Jing He, Qiaoling Dai

“…Thirdly, the model boosts classification precision through the integration of a Mixed Local Channel Attention (MLCA) strategy preceding the three detection outputs. Finally, the W-IoU loss function is utilized, which adaptively modifies the weights for different target boxes within the loss computation, to efficiently address the difficulties associated with detecting small targets. …”
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Non-invasive detection of Parkinson’s disease based on speech analysis and interpretable machine learning by Huanqing Xu, Wei Xie, Mingzhen Pang, Ya Li, Luhua Jin, Fangliang Huang, Xian Shao

“…ObjectiveParkinson’s disease (PD) is a progressive neurodegenerative disorder that significantly impacts motor function and speech patterns. …”
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LittleFaceNet: A Small-Sized Face Recognition Method Based on RetinaFace and AdaFace by Zhengwei Ren, Xinyu Liu, Jing Xu, Yongsheng Zhang, Ming Fang

“…Retinaface-Resnet is designed for face detection and localization, while adaface is employed to address low-resolution face recognition by using feature norm approximation to estimate image quality and applying an adaptive margin function. …”
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Clinical Study Support by Long-Term Stability Studies of Alpha₁-Proteinase Inhibitor and Urea in Relevant Biological Matrices by Andrea Engelmaier, Martin Zimmermann, Harald A. Butterweck, Alfred Weber

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Multi-Scenario Remote Sensing Image Forgery Detection Based on Transformer and Model Fusion by Jinmiao Zhao, Zelin Shi, Chuang Yu, Yunpeng Liu

“…This scheme won seventh place in the “Forgery Detection in Multi-scenario Remote Sensing Images of Typical Objects” track of the 2024 ISPRS TC I contest on Intelligent Interpretation for Multi-modal Remote Sensing Application.…”
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Gait-Based AI Models for Detecting Sarcopenia and Cognitive Decline Using Sensor Fusion by Rocío Aznar-Gimeno, Jose Luis Perez-Lasierra, Pablo Pérez-Lázaro, Irene Bosque-López, Marina Azpíroz-Puente, Pilar Salvo-Ibáñez, Martin Morita-Hernandez, Ana Caren Hernández-Ruiz, Antonio Gómez-Bernal, María de la Vega Rodrigalvarez-Chamarro, José-Víctor Alfaro-Santafé, Rafael del Hoyo-Alonso, Javier Alfaro-Santafé

“…<b>Background/Objectives</b>: Sarcopenia and cognitive decline (CD) are prevalent in aging populations, impacting functionality and quality of life. …”
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AI-driven pharmacovigilance: Enhancing adverse drug reaction detection with deep learning and NLP by Dr. Bharti Khemani, Dr. Sachin Malave, Samyukta Shinde, Mandvi Shukla, Razzaq Shikalgar, Harshita Talwar

“…The objective is to outperform traditional signal detection methods and provide interpretable predictions to aid clinicians in real-time. …”
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Quantifying the Sensitivity of Targeted eDNA Surveys to Improve Detection of Invasive Cane Toads (Rhinella marina) by Ewen K. Lawler, Simon Clulow, Alejandro Trujillo‐González, Paul G. Nevill, Richard P. Duncan

“…We sampled waterbodies across the invasion front and showed that both eDNA and visual surveys had similar performance in detecting cane toads. Environmental DNA sensitivity varied predictably across waterbodies as a function of several factors. …”
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Lightweight deep neural network for contour detection and extraction of wheat spikes in complex field environments by Xin Xu, Haiyang Zhang, Jiangchuan Lu, Ziyi Guo, Juanjuan Zhang, Jibo Yue, Hongbo Qiao, Xinming Ma

“…Further optimizes the loss function system by replacing traditional IoU with Scylla Intersection over Union (SIoU) metric, enhancing bounding box regression through dynamic focus factors, and adding high-resolution small-object detection layers to mitigate dense spikelet feature loss. …”
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Oak-YOLO: A high-performance detection model for automated Oak seed defect identification. by Hao Li, Zhuqi Li, Dongkui Chen, Wangyu Wu, Xuanlong He, Hongbo Mu

“…Additionally, the WIoUv3 loss function is introduced to optimize bounding box regression for complex target shapes and overlapping instances.Extensive experiments were conducted on both single-object and multi-object datasets. …”
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ESMII-Net: An edge-synergy and multidimensional information interaction network for remote sensing change detection by Yixin Chen, Xiaogang Ning, Ruiqian Zhang, Hanchao Zhang, Xiao Huang, You He

“…Furthermore, during the loss function formulation, we have incorporated a Small Object Enhancement Factor (SOEF) to prioritize small object detection. …”
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A dual-domain perception gate-controlled adaptive fusion algorithm for road crack detection by Ziyang Zhang, Yong’an Feng

“…The current object detection algorithms demonstrate deficiencies in considering feature redundancy across channel-spatial dimensions, employ indiscriminate fusion strategies for multi-stage feature information, and particularly neglect the high-frequency characteristics inherent in crack features, leading to inefficient network performance and a loss of crucial information. …”
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A Transformer-Based Detection Network for Precision Cistanche Pest and Disease Management in Smart Agriculture by Hang Zhang, Zimo Gong, Chen Hu, Canyang Chen, Zihang Wang, Boda Yu, Jingchao Suo, Chenlu Jiang, Chunli Lv

“…This study focuses on pest and disease detection in cistanche, proposing a Transformer-based object detection network enhanced by a bridging attention mechanism and bridging loss function, demonstrating outstanding performance in complex agricultural scenarios. …”
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A Diffusion-Based Detection Model for Accurate Soybean Disease Identification in Smart Agricultural Environments by Jiaxin Yin, Weixia Li, Junhong Shen, Chaoyu Zhou, Siqi Li, Jingchao Suo, Jujing Yang, Ruiqi Jia, Chunli Lv

“…This paper proposes a diffusion-based object detection model that integrates the endogenous diffusion sub-network and the endogenous diffusion loss function to progressively optimize feature distributions, significantly enhancing detection performance for complex backgrounds and diverse disease regions. …”
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The Lightweight Method of Ground Penetrating Radar (GPR) Hidden Defect Detection Based on SESM-YOLO by Yu Yan, Guangxuan Jiao, Minxing Cui, Lei Ni

“…Additionally, the SCSA attention mechanism is introduced before the detection head, enabling precise extraction of defect object features. (3) As a novel loss function, MPDIoU is proposed to reduce the disparity between the corners of the predicted bounding boxes and those of the ground truth boxes. …”
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Star-YOLO: A Lightweight Real-Time Wheat Grain Detection Model for Embedded Deployment by Zhihang Qu, Xiao Liang, Sicheng Liang, Xiumei Guo

“…With the rapid advancement of precision agriculture, traditional object detection algorithms struggle with limited efficiency and accuracy in wheat grain detection and counting, while the need for real-time deployment of deep learning models on embedded devices becomes increasingly critical. …”
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YOLO-SRW: An Enhanced YOLO Algorithm for Detecting Prohibited Items in X-Ray Security Images by Minwei Chen, Zhixian Zhang, Nian Jiang, Xingxing Li, Xin Zhang

“…Then, we integrate the Shallow Robust Feature Downsampling (SRFD) module to enhance the shallow feature extraction in YOLOv8, enhancing the model&#x2019;s ability to extract features from low-resolution and feature-sparse targets, thus reducing object information loss. Finally, by combining SCYLLA-IoU (SIoU) and Wise-IoUv3 losses, we design the Wise-SIoU loss function to reduce false negatives and false positives in Prohibited item detection, enhancing the model&#x2019;s generalization ability. …”
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