Road Damage Detection Using YOLOv7 with Cluster Weighted Distance-IoU NMS by Rudy Rachman, Nanik Suciati, Shintami Chusnul Hidayati

“…The object detection method requires post-processing for its detection results to save only the best prediction from the method, namely, non-maximum suppression (NMS). …”
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SPICE-Level Demonstration of Unsupervised Learning With Spintronic Synapses in Spiking Neural Networks by Salah Daddinounou, Anteneh Gebregiorgis, Said Hamdioui, Elena-Ioana Vatajelu

“…Unlike conventional neuromorphic hardware that relies on simple weight mapping post-off-line training, our approach emphasizes continuous, unsupervised learning, ensuring an energy efficiency of 11.2nW per synaptic update during training and as low as 109fJ/spike during inference.…”
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Transcriptome atlas of Striga germination: Implications for managing an intractable parasitic plant by Gilles Irafasha, Sylvia Mutinda, Fredrick Mobegi, Brett Hale, George Omwenga, Asela J. Wijeratne, Susann Wicke, Emily S. Bellis, Steven Runo

“…Results showed that germination proceeds immediately after SL perception and is marked by a wave of transcriptional reprogramming to allow for metabolic processes of energy mobilization. Cluster analysis using self‐organizing maps revealed a time‐phased and genotype‐differentiated response to germination stimulation. …”
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The evolutionary analysis of emerging low frequency HIV-1 CXCR4 using variants through time--an ultra-deep approach. by John Archer, Andrew Rambaut, Bruce E Taillon, P Richard Harrigan, Marilyn Lewis, David L Robertson

“…However, when generated from viral populations current mapping software is inadequate for dealing with the high levels of variation present, resulting in the potential for biased data loss. …”
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Development and Implementation of Informational Toolkits to Address Inequities in COVID-19 Testing by Sunasia Mims, Jessica Rhinehart, Melissa Ryan, Susan Driggers, Travaé Hardaway Griffith, Grace Okoro, Tiffany Osborne, Lori Brand Bateman, Janet M. Turan, Raegan H. Durant, Barbara Hansen, Gabriela R. Oates

“…Onboarding and technical training facilitated implementation in health care settings. Pre/post implementation surveys showed high perceived usefulness and feasibility of the health care toolkits. …”
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Expecting the expected – learning from the past to provide forward scenarios through geomorphic change detection, monitoring and modeling by G. Bossi, M. Cavalli, M. Mantovani, F. T. Catelan, A. Ballaera, F. Ceccotto, G. Marcato, A Pasuto

“…In 2020, a new LiDAR survey of the area allowed assessment of the sediment dynamics within the catchment through the comparison with the post-2010 event LiDAR DTM. Based on DEM of difference maps, new insight into the behaviour of the catchment emerged, which appears to be influenced both by natural processes and anthropic activities. …”
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What does the impurity variability at the microscale represent in ice cores? Insights from a conceptual approach by P. Larkman, R. H. Rhodes, N. Stoll, C. Barbante, C. Barbante, P. Bohleber, P. Bohleber

“…In order to resolve highly thinned layers and to investigate post-depositional processes, such measurements require high-resolution analysis, especially in deep ice. …”
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Propagating observation errors to enable scalable and rigorous enumeration of plant population abundance with aerial imagery by Andrii Zaiats, T. Trevor Caughlin, Jennyffer Cruz, David S. Pilliod, Megan E. Cattau, Rongsong Liu, Richard Rachman, Maisha Maliha, Donna Delparte, John D. J. Clare

“…We apply it to estimate the abundance of a foundational shrub species in post‐wildfire landscapes in the western United States. …”
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A Robotic Prosthetic Hand for Computer Mouse Operations by Ziming Chen, Yiming He, Boao Li, Huasong Min, Fuchun Sun, Shuguang Li, Bin Fang

“…It enables an enveloping grasp of the computer mouse and facilitates diverse finger‐based clicking and scrolling operations. In addition, a mapping between the hand movements (myoelectric signals) and the computer mouse operations is created by combining a neural network classifier and a post‐processing algorithm. …”
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YOLO-LPSS: A Lightweight and Precise Detection Model for Small Sea Ships by Liran Shen, Tianchun Gao, Qingbo Yin

“…The characteristics of YOLO-LPSS are as follows: (1) Strengthening the backbone’s ability to extract and emphasize features relevant to small ship objects, particularly in semantic-rich layers. (2) A sophisticated, learnable method for up-sampling processes is employed, taking into account both deep image information and semantic information. (3) Introducing a post-processing mechanism in the final output of the resampling process to restore the missing local region features in the high-resolution feature map and capture the global-dependence features. …”
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Evaluation of seasonal variation of groundwater quality by using the correlation matrices method in Koppal Taluk, Karnataka, India by Ramesh Basanagouda, Avinash Pandurang, Maradi Nayaka

“…Factor analysis suggested the first three principal components (PCs) in this analysis were 96% (Monsoon), 93.50% (Pre-Monsoon), and 87% (Post-Monsoon) of the cumulative variance correspondingly, and TDS was the most representative variable across all seasons.  …”
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Transformer-Based Multi-Target Object Detection and Tracking Framework for Robust Spatio-Temporal Memory in Dynamic Environments by Tareq Mahmod AlZubi, Umar Raza Mukhtar

“…The Target Proposal Module generates object candidates using a transformer encoder-decoder structure, and the memory decoder integrates both proposal and track vectors to predict object locations and identities in real-time, minimizing post-processing. The framework incorporates a multi-scale attention pyramid to handle variations in object scale and utilizes a deformable transformer for generating accurate object proposals. …”
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R-Sparse R-CNN: SAR Ship Detection Based on Background-Aware Sparse Learnable Proposals by Kamirul Kamirul, Odysseas A. Pappas, Alin M. Achim

“…The adoption of sparse proposals streamlines the pipeline by eliminating the need for proposal generators and post-processing for overlapping predictions. The proposed BAPs enrich object representation by integrating ship and background features, allowing the model to learn their contextual relationships for more accurate distinction of ships in complex environments. …”
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Multi-layer obstacle-avoiding rectilinear steiner minimal tree algorithm based on deep reinforcement learning by Xing Huang, Yuhan Zhu, Yanbo Xu, Yajun Xie, Genggeng Liu

“…Then, an agent is designed to learn edge selection for constructing the Multi-Layer Obstacle-Avoiding Steiner Tree (ML-OAST) using Double Deep Q-Network (DDQN). Finally, a post-processing stage is applied to further shorten the total wirelength through fast pruning and local optimization. …”
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Survival of <i>Listeria monocytogenes</i> in Light and Full-Fat, Modified Atmosphere-Packaged, Sliced Greek Cheese over Shelf Life: Implications for Ready-to-Eat Food Safety by Ntina Vasileiadi, Theofania Tsironi, Georgia D. Mandilara

“…The observed survival highlights the importance of growth potential assessment, even in food matrices seemingly non-supportive of <i>Lm</i>. Given that post-pasteurization processing steps like slicing and MAP packaging can introduce contamination risks for vulnerable consumers, this study emphasizes the necessity of stringent hygienic practices to prevent <i>Lm</i> contamination. …”
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Multi-Level Intertemporal Attention-Guided Network for Change Detection in Remote Sensing Images by Shuo Liu, Qinyu Zhang, Yuhang Zhang, Xiaochen Niu, Wuxia Zhang, Fei Xie

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Drone-Based VNIR–SWIR Hyperspectral Imaging for Environmental Monitoring of a Uranium Legacy Mine Site by Victor Tolentino, Andres Ortega Lucero, Friederike Koerting, Ekaterina Savinova, Justus Constantin Hildebrand, Steven Micklethwaite

“…However, its accuracy is limited when mapping specific minerals, as most endmembers represent mineral groups or mixtures. …”
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YOLO-SAG: An improved wildlife object detection algorithm based on YOLOv8n by Lingli Chen, Gang Li, Shunkai Zhang, Wenjie Mao, Mei Zhang

“…Inference and post-processing times reach 1.2 ms and 0.5 ms, a speedup of 25% and 54.5%, respectively, and the computation volume is only 7.2 GFLOPs, an 11.1% decrease.…”
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Autonomous Aerial Vehicle Object Detection Based on Spatial Perception and Multiscale Semantic and Detail Feature Fusion by Wei Rao, Siyuan Chen, Dan Li

“…Finally, a method that integrates Soft Non-Maximum Suppression (Soft-NMS) with Generalized Intersection over Union (GIoU), called GIoU-Soft-NMS, is proposed to enhance the model&#x2019;s post-processing capability and reduce the missed and false detection rates, thereby further improving the detection accuracy of the model. …”
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A Novel Geometric-Descriptor Based Algorithm for Individual-Level Crop Monitoring using UAVs by Y. Goswami, Y. Goswami, N. Ramprasad, S. N. Omkar

“…GPS offers a potential solution by tagging each crop with a unique coordinate feature for mapping, but GPS-based systems like Real-Time Kinematic and Post-Processed Kinematic are costly, complex, and struggle on uneven terrains. …”
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