Highly Robust Synthetic Aperture Radar Target Recognition Method Based on Simulation Data Training by Liping Hu, Canming Yao, Jian Huang, Jinfan Liu, Guanyong Wang

“…There are inevitable differences between the simulated and measured SAR images, which will affect the recognition performance. …”
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Mapping herbaceous wetlands using combined phenological and hydrological features from time-series Sentinel-1/2 imagery by Zhaolong Yang, Xiaodong Na

“…However, the classification results of herbaceous marshes differ significantly using single date imagery because of the different vegetation phenological rhythm and hydrological condition. …”
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Category semantic and global relation distillation for object detection by Yanpeng LIANG, Zhonggui MA, Zongjie WANG, Zhuo LI

“…These objects often exhibit variations in scale, intricate interclass relationships, and are dispersed across different locations. These factors make it difficult to balance the contributions of different elements, such as bounding box centers and backgrounds during distillation. …”
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A Generalized Zero-Shot Deep Learning Classifier for Emotion Recognition Using Facial Expression Images by Vishal Singh Bhati, Namita Tiwari, Meenu Chawla

“…Zero-shot classification is performed on different facial expression datasets to justify the generalizability of the proposed model. …”
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Dynamic Scene Segmentation and Sentiment Analysis for Danmaku by Limin Li, Jie Jing, Peng Shi

“…With this as a base, a new Danmaku-E model is made to find and group seven different emotional categories within Danmaku comments. …”
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Quality prediction of air-cured cigar tobacco leaf using region-based neural networks combined with visible and near-infrared hyperspectral imaging by Jianxun Yin, Jun Wang, Jian Jiang, Jian Xu, Liang Zhao, Anfu Hu, Qian Xia, Zhihan Zhang, Ming Cai

“…Specifically, the quality of cigar tobacco leaves undergoes subtle changes due to environmental differences during the air-curing phase. This study aims to evaluate the feasibility of deep learning methods in overcoming data limitations to develop a VNIR-HSI prediction model for the quality of cigar tobacco leaves at different air-curing levels. …”
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Using a Solution Construction Algorithm for Cyclic Shift Network Coding under Multicast Network to the Transformation of Musical Performance Styles by Xiuqin Wang, Jun Geng, Zhiyuan Li

“…A two-way recurrent neural network based on the gated recurrent unit is used to extract a sequence of note feature vectors of different styles, and a one-dimensional convolutional neural network is used to predict the intensity of the extracted note feature vector sequence for a specific style, which better learns the intensity variation of different styles of MIDI music.…”
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AI-based orchard monitoring at night: Enhancing sustainable fruit production through real-time apple detection by Kutyrev Alexey, Khort Dmitry, Smirnov Igor, Zubina Valeria

“…Accurate recognition, classification and segmentation of apple fruits on tree crowns are of key importance for improving the efficiency of remote monitoring and forecasting of fruit orchard yields at different stages of the production process. The study evaluates the performance of the state-of-the-art convolutional neural network model YOLO11 (You Only Look Once version 11) under artificial lighting conditions at night. …”
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Prediction of COVID-19 cases by multifactor driven long short-term memory (LSTM) model by Yanwen Shao, Tsz Kin Wan, Kei Hang Katie Chan

“…Through the selection of several important features, we identified the factors that have stronger impact on the increase of new cases in different groups. Then, we use a long-time span data to predict the future COVID-19 new cases by training a long short-term memory (LSTM) model, a support vector regressor (SVR) and a temporal convolutional network (TCN), among which LSTM possessed the best performance and offered a good generalization ability. …”
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Image retrieval method based on data mining and deep residual network by Hongzhi Yuan, Wei Hu

“…The experimental results showed that the improved model achieved an average retrieval accuracy of 81.1 % on three different image sets, which was 27 percentage points higher than that of the traditional model. …”
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Pilot Maneuvering Performance Analysis and Evaluation with Deep Learning by Shiwen Zhang, Zhimei Huo, Yanjin Sun, Fujuan Li, Bo Jia

“…Finally, the indicators were grouped into 5 common factors by factor analysis and fed into 1-D CNN in different combinations. Each common factor plays a different role in pilot performance evaluation, which can provide advice for the future.…”
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Real-time Jordanian license plate recognition using deep learning by Salah Alghyaline

“…Countries have different specifications for License Plates (LPs), therefore developing one Automatic license plate recognition (ALPR) system that works well for all LPs types is a difficult task. …”
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MDS-Net: An Image-Text Enhanced Multimodal Dual-Branch Siamese Network for Remote Sensing Change Detection by Tao Wang, Tiecheng Bai, Chao Xu, Erlei Zhang, Bin Liu, Xining Zhao, Hongming Zhang

“…Remote sensing change detection (RSCD), which aims to identify differences between bitemporal images, has made great progress through the application of deep learning methods. …”
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Do comprehensive deep learning algorithms suffer from hidden stratification? A retrospective study on pneumothorax detection in chest radiography by Luke Oakden-Rayner, Catherine M Jones, John Lambert, Jarrel Seah, Cyril Tang, Quinlan D Buchlak, Michael Robert Milne, Xavier Holt, Hassan Ahmad, Nazanin Esmaili, Peter Brotchie

“…The hypothesis was that performance would not differ significantly in each of these subgroups when compared with the overall test dataset.Design A retrospective case–control study was undertaken.Setting Community radiology clinics and hospitals in Australia and the USA.Participants A test dataset of 2557 chest radiography studies was ground-truthed by three subspecialty thoracic radiologists for the presence of simple or tension pneumothorax as well as each subgroup other than positioning. …”
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Enhanced multiscale plant disease detection with the PYOLO model innovations by Yirong Wang, Yuhao Wang, Jiong Mu, Ghulam Raza Mustafa, Qianqian Wu, Ying Wang, Bi Zhao, Siyue Zhao

“…Additionally, the model’s ability to focus on different parts of the image is improved by redesigning the EC2f structure and dynamically adjusting the convolutional kernel size to better capture features at various scales. …”
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Retraining and evaluation of machine learning and deep learning models for seizure classification from EEG data by Juan Pablo Carvajal-Dossman¹, Laura Guio, Danilo García-Orjuela, Jennifer J. Guzmán-Porras, Kelly Garces, Andres Naranjo, Silvia Juliana Maradei-Anaya, Jorge Duitama

“…However, manual annotation of seizures in EEG data is a major time-consuming step in the analysis process of EEGs. Different machine learning models have been developed to perform automated detection of seizures from EEGs. …”
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A prototype-based rockburst types and risk prediction algorithm considering intra-class variance and inter-class distance of microseismic data by Xiufeng Zhang, Guoying Li, Yang Chen, Hao Wang, Haikuan Zhang, Haitao Li, Weisheng Du, Xiao Li, Xuewei Xu, Yuze He

“…The results show that the distribution features may be different for the same type of microseismic (MS) and rockburst events, and different types of events may show similar distribution features. …”
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A hybrid model based on CNN-LSTM for assessing the risk of increasing claims in insurance companies by Walaa Gamaleldin, Osama Attayyib, Mrim M. Alnfiai, Faiz Abdullah Alotaibi, Ruixing Ming

“…The results demonstrate that the model effectively classifies insurance risks in different market environments, highlighting its potential for real-world applications. …”
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Driver Steering Intention Prediction for Human-Machine Shared Systems of Intelligent Vehicles Based on CNN-GRU Network by Chen Zhou, Fan Zhang, Edric John Cruz Nacpil, Zheng Wang, Fei-Xiang Xu

“…The proposed prediction method also possesses adaptability to different driver behaviors.…”
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FAULT DIAGNOSIS OF GEARBOX UNDER VARIABLE WORKING CONDITION BASED ON WEIGHTED SUBDOMAIN ADAPTIVE ADVERSARIAL NETWORK by ZHANG Huiyun, ZUO Fangjun, YU Xi, YANG Ting

“…Subsequently, a self-calibrated convolutions network (SCNet) incorporating an efficient channel attention (ECA) mechanism acted as a feature extractor, dynamically adjusting the interactions and dependencies between multi-source heterogeneous signals to balance the scale differences between the source and target domain heterogeneous data. …”
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