Enhancing UAV Object Detection in Low-Light Conditions with ELS-YOLO: A Lightweight Model Based on Improved YOLOv11 by Tianhang Weng, Xiaopeng Niu

“…ELS-YOLO features a re-parameterized backbone (ER-HGNetV2) with integrated Re-parameterized Convolution and Efficient Channel Attention mechanisms, a Lightweight Feature Selection Pyramid Network (LFSPN) for multi-scale object detection, and a Shared Convolution Separate Batch Normalization Head (SCSHead) to reduce computational complexity. …”
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ClimSat – A diffusion autoencoder model for climate-conditional satellite image editing by Johannes Leonhardt, Juergen Gall, Ribana Roscher

“…The proposed ClimSat model is constructed as a diffusion autoencoder, and it incorporates contextual information through multi-conditional batch normalization and classifier-free guidance. …”
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Spawning in the deep: reproductive life history of four mesopelagic fishes of the northwestern Atlantic Ocean by Lyndsey S. Lefebvre, Heidi M. Sosik, Joel K. Llopiz

“…S. beanii were found to be gonochoristic, iteroparous, and likely have multi-year oocyte development with an L50 of 90.38 mm. …”
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Model and algorithm of the billet design problem in the production of seamless steel tubes with a single billet size by LI Tie-ke, LIU Yu-zhuo, WANG Bai-lin, LUAN Zhi-wei

“…The billet design problem (BDP) in seamless steel tube production is to assign order tubes to billets under process constraints. Because of the batch rule in practical production, each order has a minimum weight of tubes assigned to any billet. …”
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Optimization of Ultrasonic Extraction of Total Flavonoids from Cinnamonum zeylaniccum by Seyma Balcı, Sibel Yiğitarslan

“…Multi-parameter optimization was carried out with three-parameter, three-level, three-centered Box-Behnken design considering the optimum values obtained in single-parameter optimization. …”
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Simulation and Prediction of Springback in Sheet Metal Bending Process Based on Embedded Control System by Jinhan Xu, Jun Yan, Yan Huang, Dawei Ding

“…Amidst the accelerating pace of automation in sheet metal bending, the need for small-batch, multi-varietal, efficient, and adaptable production modalities has become increasingly pronounced. …”
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Model reduction of structural mechanical response in the time domain by Xin Yan, Xinyu Guo, Ningya He, Jinglong Shi, Daquan Zhao

“…A hyperparameter tuning and optimization procedure for neural network models is proposed, exploring batch size, hidden layer type, activation function, cells number, epochs number, and number of hidden layers. …”
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Intracellular Cytokine Staining and Flow Cytometry: Considerations for Application in Clinical Trials of Novel Tuberculosis Vaccines. by Steven G Smith, Kaatje Smits, Simone A Joosten, Krista E van Meijgaarden, Iman Satti, Helen A Fletcher, Nadia Caccamo, Francesco Dieli, Francoise Mascart, Helen McShane, Hazel M Dockrell, Tom H M Ottenhoff, TBVI TB Biomarker Working Group

“…In the case of sample material, frozen PBMC, despite some loss of sensitivity, may be more advantageous for batch analysis. We also recommend that for multi-site studies, common antibody panels, gating strategies and analysis approaches should be employed for better comparability.…”
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Kinetic Investigation of the Asymmetric Hydrogenation of Benzylphenylephrone in Continuous Flow by Maurice Moll, Björn Wängler, Carmen Wängler, Thorsten Röder

“…However, traditional production methods are often dominated by multi-purpose batch processes and empirical development approaches. …”
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Robust low threshold full-color upconversion lasing in rare-earth activated nanocrystal-in-glass microcavity by Zhigang Gao, Lugui Cui, Yushi Chu, Luyue Niu, Lehan Wang, Rui Zhao, Yulong Yang, Xiaofeng Liu, Jing Ren, Guoping Dong

“…These multi-phase composite microspheres exhibit a high Q value (≥105), comparable to that of conventional multi-component glass microspheres. …”
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Intelligent library shelf management system for open-access environments: A CNN-based approach with enhanced image recognition and disorder detection by Xueqi Zhang

“…The new system adopts an optimized convolutional kernel design to improve the accuracy of feature extraction. It incorporates batch normalization techniques to mitigate the occurrence of overfitting and utilizes multi-scale feature fusion technology to enhance the ability to recognize book images. …”
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Fault Line Selection of Single Phase Grounding Based on Wavelet Packet Full Frequency Analysis and OS-ELM by JI Wen-lu, ZHAO Xiao-long, ZHANG Ming, YANG Hong-lei, WENG Jia-ming

“…In this paper，the fault characteristics of fault transient signals are extracted by using the multi-resolution frequency division characteristics of wavelet packets. …”
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Highly parallel optimisation of chemical reactions through automation and machine intelligence by Joshua W. Sin, Siu Lun Chau, Ryan P. Burwood, Kurt Püntener, Raphael Bigler, Philippe Schwaller

“…Minerva demonstrates robust performance with experimental data-derived benchmarks, efficiently handling large parallel batches, high-dimensional search spaces, reaction noise, and batch constraints present in real-world laboratories. …”
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Comprehensive Micromagnetic Modeling: Practical Techniques, Applications, and Emerging Challenges by Ahmet Bahadir Trabzon, Taichi Goto, Mehmet Cengiz Onbasli

“…Finally, the tutorial addresses micromagnetic modeling limitations in capturing quantum effects, multi-domain couplings, and temperature-dependent phenomena. …”
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Cluster-independent multiscale marker identification in single-cell RNA-seq data using localized marker detector (LMD) by Ruiqi Li, Rihao Qu, Fabio Parisi, Francesco Strino, Hainan Lam, Jay S. Stanley, Xiuyuan Cheng, Peggy Myung, Yuval Kluger

“…Localized Marker Detector (LMD) is a novel tool to identify “localized genes”—genes exclusively expressed in groups of highly similar cells—thereby characterizing cellular diversity in a multi-resolution and fine-grained manner. LMD constructs a cell-cell affinity graph, diffuses the gene expression value across the cell graph, and assigns a score to each gene based on its diffusion dynamics. …”
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A deep neural network for tactile perception in open scenes by Huirong Fang, Qianhui Yang, Kunhong Liu, Xiangyi Huang, Yu Xie

“…To handle this problem, different from the former studies of tactile perception in enclosed environments, this study focuses on the tactile material recognition task using robot electronic skin in open scenes. We construct a cross-batch tactile dataset to simulate open scenes and propose the multi-receptive field attention enhancement network (MRFE) to handle tactile material recognition. …”
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Deep learning method for cucumber disease detection in complex environments for new agricultural productivity by Jun Liu, Xuewei Wang, Qian Chen, Peng Yan, Xin Liu

“…Abstract Cucumber disease detection under complex agricultural conditions faces significant challenges due to multi-scale variation, background clutter, and hardware limitations. …”
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Optimized Deep Learning for Mammography: Augmentation and Tailored Architectures by Syed Ibrar Hussain, Elena Toscano

“…Multiple DCNN models were tested to see how well deep learning worked for difficult, multi-class categorization problems. These models were trained on pre-processed datasets with optimized hyperparameters (e.g., the batch size, learning rate, and dropout) which increased the precision of classification. …”
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Advanced Sales Route Optimization Through Enhanced Genetic Algorithms and Real-Time Navigation Systems by Wilmer Clemente Cunuhay Cuchipe, Johnny Bajaña Zajia, Byron Oviedo, Cristian Zambrano-Vega

“…Future work will explore parallelization strategies and multi-objective extensions for sustainability-aware routing.…”
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RSPS-SAM: A Remote Sensing Image Panoptic Segmentation Method Based on SAM by Zhuoran Liu, Zizhen Li, Ying Liang, Claudio Persello, Bo Sun, Guangjun He, Lei Ma

“…Firstly, to address the problem of global information loss caused by cropping large remote sensing images for training, a Batch Attention Pyramid was designed to extract multi-scale features from remote sensing images and capture long-range contextual information between cropped patches, thereby enhancing the semantic understanding of remote sensing images. …”
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