Robot assisted sentinel lymph node biopsy using indocyanine green combined with carbon nanoparticles staining improved detection rates in breast cancer by Qinbo Wang, Qingyu Yang, Zuxiao Chen, Zongyan Li, Xiaoyan Fu, Yunxiang Luo, Yonghai Guo, Haiyan Li

“…Robot-assisted sentinel lymph node biopsy is an effective procedure for breast cancer, dual staining may facilitate improved detection rates pertaining to occult sentinel lymph node metastasis warranting further clinical exploration.…”
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Occurrence of Tomato Brown Rugose Fruit Virus in Lorestan Province Tomato Greenhouses: A First Report by Leila Baharvand, Samira Pakbaz, Farshad Rakhshandehroo, Forough Sanjarian, Ehsan Hasanvand

“…This report represents the first documented ToBRFV detection instance in Lorestan Province tomato greenhouses.…”
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H-Alpha anomalyzer: An anomaly detector for H-Alpha solar observations using a grid-based approach by Mahsa Khazaei, Heba Mahdi, Kartik Chaurasiya, Azim Ahmadzadeh

“…This article presents a Python package named H-Alpha Anomalyzer for detecting anomalous H-Alpha observations of the Sun. …”
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Food Fraud in Plant-Based Proteins: Analytical Strategies and Regulatory Perspectives by Jun-Hyeok Ham, Yeon-Jung Lee, Seung-Su Lee, Hae-Yeong Kim

“…Despite these challenges, most efforts toward preventing food fraud and developing detection technologies have largely focused on animal-based products, with limited attention given to plant-based proteins. …”
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Multi-scale eddy identification and analysis based on deep learning method and ocean color data by Meng Hou, Lixing Fang, Kai Wu, Jie Yang, Ge Chen

“…Owing to the spatial resolution limitations of altimeters, the detection of submesoscale eddies remains challenging. …”
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Explainable artificial intelligence driven insights into smoking prediction using machine learning and clinical parameters by S. Aishwarya, P. C. Siddalingaswamy, Krishnaraj Chadaga

“…These impacts underscore the need for early detection of smoking status to enable timely intervention. …”
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LensNet: Enhancing Real-time Microlensing Event Discovery with Recurrent Neural Networks in the Korea Microlensing Telescope Network by Javier Viaña, Kyu-Ha Hwang, Zoë de Beurs, Jennifer C. Yee, Andrew Vanderburg, Michael D. Albrow, Sun-Ju Chung, Andrew Gould, Cheongho Han, Youn Kil Jung, Yoon-Hyun Ryu, In-Gu Shin, Yossi Shvartzvald, Hongjing Yang, Weicheng Zang, Sang-Mok Cha, Dong-Jin Kim, Seung-Lee Kim, Chung-Uk Lee, Dong-Joo Lee, Yongseok Lee, Byeong-Gon Park, Richard W. Pogge

“…Our system operates in conjunction with a preliminary algorithm that detects increasing trends in flux. These flagged instances are then passed to LensNet for further classification, allowing for timely alerts and follow-up observations. …”
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MSFNet3D: Monocular 3D Object Detection via Dual-Branch Depth-Consistent Fusion and Semantic-Guided Point Cloud Refinement by Rong Yang, Zhijie You, Renhui Luo

“…This approach reduces feature conflicts within the dual-branch network and enhances the model’s robustness in complex scenes. (3) We introduce a semantic-guided pseudo-point cloud enhancement method that leverages an instance segmentation network to extract object-specific semantic regions and generate high-confidence point cloud, consequently improving the accuracy of object detection. …”
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Infra-3DRC-FusionNet: Deep Fusion of Roadside Mounted RGB Mono Camera and Three-Dimensional Automotive Radar for Traffic User Detection by Shiva Agrawal, Savankumar Bhanderi, Gordon Elger

“…These anchors guide the prediction of 2D bounding boxes, object categories, and confidence scores. Valid detections are then used to segment radar points by instance, and the results are post-processed to produce final road user detections in the ground plane. …”
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A Method for Predicting Coal-Mine Methane Outburst Volumes and Detecting Anomalies Based on a Fusion Model of Second-Order Decomposition and ETO-TSMixer by Qiangyu Zheng, Cunmiao Li, Bo Yang, Zhenguo Yan, Zhixin Qin

“…Furthermore, we propose an anomaly detection framework based on STL decomposition and dual lonely forests. …”
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Comparative Global Assessment and Optimization of LandTrendr, CCDC, and BFAST Algorithms for Enhanced Urban Land Cover Change Detection Using Landsat Time Series by Taku Murakami, Narumasa Tsutsumida

“…Our findings underscore that parameter optimization and band selection significantly impact detection accuracy, with variations up to 30% observed across different configurations. …”
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Real-time fire and smoke detection system for diverse indoor and outdoor industrial environmental conditions using a vision-based transfer learning approach by Uttam U. Deshpande, Goh Kah Ong Michael, Sufola Das Chagas Silva Araujo, Sowmyashree H. Srinivasaiah, Harshel Malawade, Yash Kulkarni, Yash Desai

“…Performance benchmarks on fire instances such as mAP@0.5 (94.9%), mAP@0.5:0.95 (87.4%), and a low false rate of 3.5% highlight the DetectNet_v2 framework’s robustness and superior detection performance. …”
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Optimization of Filter Considering Harmonic Resonance in the Distribution Network by XIA Xiangyang, XU Linju, LUO Shiwu

“…Results show that the method of the resonance detection principle is used to optimize the configuration of the filter obtaining a good filtering effect, avoiding the resonance occurrence and demonstrate the feasibility of the method by Matlab simulation and instance validation.…”
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Detecting Conversation Topics in Recruitment Calls of African American Participants to the All of Us Research Program Using Machine Learning: Model Development and Validation Study by Priscilla Pemu, Michael Prude, Atuarra McCaslin, Elizabeth Ojemakinde, Christopher Awad, Kelechi Igwe, Anny Rodriguez, Jasmine Foriest, Muhammed Idris

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key-fg DETR based camouflaged locust objects in complex fields by Dongmei Chen, Peipei Cao, Zhihua Diao, Yingying Dong, Jingcheng Zhang

“…IntroductionIn real agricultural environments, many pests camouflage themselves against complex backgrounds, significantly increasing detection difficulty. This study addresses the challenge of camouflaged pest detection.MethodsWe propose a Transformer-based detection framework that integrates three key modules: 1.Fine-Grained Score Predictor (FGSP) – guides object queries to potential foreground regions; 2.MaskMLP generates instance-aware pixel-level masks; 3.Denoising Module and DropKey strategy – enhance training stability and attention robustness.ResultsEvaluated on the COD10k and Locust datasets, our model achieves AP scores of 36.31 and 75.07, respectively, outperforming Deformable DETR by 2.3% and 3.1%. …”
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KRID: A Large-Scale Nationwide Korean Road Infrastructure Dataset for Comprehensive Road Facility Recognition by Hyeongbok Kim, Eunbi Kim, Sanghoon Ahn, Beomjin Kim, Sung Jin Kim, Tae Kyung Sung, Lingling Zhao, Xiaohong Su, Gilmu Dong

“…To demonstrate the utility of this resource, we conducted object detection and segmentation experiments using YOLO-based models, focusing on guardrail damage detection and traffic sign recognition. …”
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Application of YOLO11 Model with Spatial Pyramid Dilation Convolution (SPD-Conv) and Effective Squeeze-Excitation (EffectiveSE) Fusion in Rail Track Defect Detection by Weigang Zhu, Xingjiang Han, Kehua Zhang, Siyi Lin, Jian Jin

“…With the development of the railway industry and the progression of deep learning technology, object detection algorithms have been gradually applied to track defect detection. …”
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Enhanced Detection Performance of Acute Vertebral Compression Fractures Using a Hybrid Deep Learning and Traditional Quantitative Measurement Approach: Beyond the Limitations of Ge... by Jemyoung Lee, Minbeom Kim, Heejun Park, Zepa Yang, Ok Hee Woo, Woo Young Kang, Jong Hyo Kim

“…The complementary use of DL methods with HLR further improved detection performance. For instance, combining HLR-negative cases with TSVD_SD increased sensitivity to 87.84%, reducing missed fractures, while combining HLR-positive cases with EEVD achieved the highest specificity (99.77%), minimizing false positives. …”
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Comparative Study of MiroCam MC2000 and PillCam SB3 in Detecting Small Bowel Bleeding: A Multicenter Prospective Randomized Crossover Study by Ji Eun Kim, Eun Ran Kim, Jae Jun Park, Kyeong Ok Kim, Yehyun Park, Young Joo Yang, Hyun Joo Jang

“…Minor complications included device stasis, with fewer incidents with the MC2000 than with the SB3, and one instance of small bowel retention due to ulcers. Conclusions : The MC2000’s dual-camera system appears to enhance the detection of small bowel lesions over the SB3, especially for more important lesions. …”
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TFDGiniXML: A Novel Explainable Machine Learning Framework for Early Detection of Cardiac Abnormalities Based on Nonlinear Time-Frequency Distribution Gini Index Features by Mohamed Aashiq, Shaiful Jahari Hashim, Fakhrul Zaman Rokhani, Marsyita Hanafi, Ahmed Faeq Hussein

“…This study proposes explainable intelligent classifiers incorporated with a novel sequence of time-frequency energy Gini Index (GI) features from the QRS complexes of ECG signals to address these challenges and enable early-stage CVD detection. These features are extracted using the Choi-Williams Time-Frequency method, reporting the first instance application of GI measures to nonlinear time-frequency distribution (TFD) for ECG analysis. …”
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