Integrating Deep Learning and Transcriptomics to Assess Livestock Aggression: A Scoping Review by Roland Juhos, Szilvia Kusza, Vilmos Bilicki, Zoltán Bagi

“…The main developments include convolutional neural network (CNN)-based object detection and pose estimation systems, together with the transcriptomic identification of molecular pathways that link to aggression and stress. …”
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Nondestructive Detection of Rice Milling Quality Using Hyperspectral Imaging with Machine and Deep Learning Regression by Zhongjie Tang, Shanlin Ma, Hengnian Qi, Xincheng Zhang, Chu Zhang

“…Most multi-task models demonstrated a higher prediction accuracy compared with their corresponding single-task models. …”
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A novel approach for multiclass sentiment analysis on Chinese social media with ERNIE-MCBMA by Youyang Sun, Ziyi Yu, Yuyu Sun, Yaqing Xu, Boming Song

“…Abstract Weibo, one of the most widely used social media platforms in China, sees a vast number of users expressing their opinions and emotional tendencies. …”
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Progressive multi-scale multi-attention fusion for hyperspectral image classification by Hu Wang, Sixiang Quan, Jun Liu, Hai Xiao, Yingying Peng, Zhihui Wang, Huali Li

“…Although hyperspectral image classification methods based on convolutional neural networks (CNN) have noticeably improved performance, there are still certain shortcomings in the extraction of detailed and local features. …”
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Surface and Subsurface Soil Moisture Estimation Using Fusion of SMAP, NLDAS-2, and SOLUS100 Data with Deep Learning by Saman Rabiei, Ebrahim Babaeian, Sabine Grunwald

“…The model also performed in estimating subsurface SM than surface SM for most land-cover types. Incorporating SMAP ancillary data and SOLUS100 digital soil maps into the ConvLSTM improved the spatial and temporal estimation of surface and subsurface SM. …”
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A Novel Metaheuristic-Based Methodology for Attack Detection in Wireless Communication Networks by Walaa N. Ismail

“…The framework used involves developing a lightweight model based on a convolutional neural network with 11 layers, referred to as CSO-2D-CNN, which demonstrates fast learning rates and excellent generalization capabilities. …”
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Effects of Automatic Hyperparameter Tuning on the Performance of Multi‐Variate Deep Learning‐Based Rainfall Nowcasting by Amirmasoud Amini, Mehri Dolatshahi, Reza Kerachian

“…In this paper, deep neural networks (DNNs) and numerical weather predictions (NWPs) are applied for rainfall and runoff forecasting in an urban catchment with a complex drainage system. DNNs are among the most accurate models for rainfall nowcasting. However, the design and training of DNNs are usually complicated. …”
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Self-Supervised Keypoint Learning for the Geometric Analysis of Road-Marking Templates by Chayanon Sub-r-pa, Rung-Ching Chen

“…Ablation studies reveal that the number of keypoints (K) impacts the performance, with K = 3 providing the most suitable balance for the overall alignment accuracy, although the performance varies across different template geometries. …”
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Multi-model Approach for Tree Detection and Classification in Wallonia Region (Belgium) by N. Dimarco, B. Bartiaux, L. Andreani, R. Schlögel

“…A Faster R-CNN model trained for tree detection achieved a F1 score of 0.828 and a mAP@50 of 0.827, effectively locating tree crowns under varying illumination and phenological conditions. Meanwhile, a convolutional neural network (CNN) for species classification attained an overall accuracy of 0.937, accurately distinguishing most species and age classes. …”
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UniFlow: Unified Normalizing Flow for Unsupervised Multi-Class Anomaly Detection by Jianmei Zhong, Yanzhi Song

“…Multi-class anomaly detection is more efficient and less resource-consuming in industrial anomaly detection scenes that involve multiple categories or exhibit large intra-class diversity. However, most industrial image anomaly detection methods are developed for one-class anomaly detection, which typically suffer significant performance drops in multi-class scenarios. …”
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Modeling Terrestrial Net Ecosystem Exchange Based on Deep Learning in China by Zeqiang Chen, Lei Wu, Nengcheng Chen, Ke Wan

“…The results show that the normalized difference vegetation index, the enhanced vegetation index, and the leaf area index play a dominant role at most sites. This study provides new ideas and methods for analyzing the intricate relationship between NEE and environmental factors by introducing the SHAP interpretable model. …”
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Micro-Mobility Safety Assessment: Analyzing Factors Influencing the Micro-Mobility Injuries in Michigan by Mining Crash Reports by Baraah Qawasmeh, Jun-Seok Oh, Valerian Kwigizile

“…The results suggest that roads with speed limits exceeding 40 mph are the most significant factor in determining the severity of micro-mobility injuries. …”
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Enhancing Stock Price Forecasting with CNN-BiGRU-Attention: A Case Study on INDY by Madilyn Louisa, Gumgum Darmawan, Bertho Tantular

“…The method applied a hybrid model combining a Convolutional Neural Network (CNN), Bidirectional Gated Recurrent Unit (BiGRU), and an Attention Mechanism (AM) to address the nonlinear, volatile, and noisy characteristics of stock data. …”
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UETT4K Anti-UAV: A Large Scale 4K Benchmark Dataset for Vision-Based Drone Detection in High-Resolution Imagery by Mughees Sarwar Awan, Syed Azhar Ali Zaidi, Junaid Mir

“…The test results and qualitative analysis guide selecting the most suitable model for drone detection applications. …”
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Modeling energy consumption indexes of an industrial cement ball mill for sustainable production by Saeed Chehreh Chelgani, Rasoul Fatahi, Ali Pournazari, Hamid Nasiri

“…The airlift current and separator variables ranked the most effective operating factors on the mill energy consumption indexes. …”
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Enhancing breast cancer prediction through stacking ensemble and deep learning integration by Fatih Gurcan

“…Breast cancer is one of the most common types of cancer in women and is recognized as a serious global public health issue. …”
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Comparison, optimization and application of multiple prestack inversion algorithm for intermediate basic volcanic reservoirs: A case study of Huoshiling Formation in Chaganhua area by LI Ruilei,CAO Lei,FAN Xuepei,FENG Xiaohui,LI Ning

“…Currently, the most widely used pre-stack simultaneous inversion algorithm is based on the Zoeppritz equation approximation of isotropic horizontal media. …”
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AI-Assisted identification of sex-specific patterns in diabetic retinopathy using retinal fundus images. by Parsa Delavari, Gulcenur Ozturan, Eduardo V Navajas, Ozgur Yilmaz, Ipek Oruc

“…Regular monitoring is crucial for detecting early signs of referable DR, and the progression to moderate to severe non-proliferative DR, proliferative DR (PDR), and macular edema (ME), the most common cause of vision loss in DR. Currently, aside from considerations during pregnancy, sex is not factored into DR diagnosis, management or treatment. …”
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State of Charge Estimation in Li-Ion Batteries Using a Parallel LSTM-Based Approach: The Impact of Modeling Based on Operating States by Osman Ozer, Hayri Arabaci

“…Deep learning has emerged as one of the most widely used approaches in machine learning. …”
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Vertically Recurrent Neural Networks for Sub‐Grid Parameterization by P. Ukkonen, M. Chantry

“…We achieve near‐perfect offline accuracy, and the forecast skill of a suite of global weather simulations using the emulator are for the most part statistically indistinguishable from reference runs. …”
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