Link Aggregation for Skip Connection–Mamba: Remote Sensing Image Segmentation Network Based on Link Aggregation Mamba by Qi Zhang, Guohua Geng, Pengbo Zhou, Qinglin Liu, Yong Wang, Kang Li

“…This module facilitates nonlinear modeling across different channels and spaces through multipath activation, catering to international and local long-range dependencies. …”
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Deep Learning-Based Invalid Point Removal Method for Fringe Projection Profilometry by Nan He, Jiachun Huang, Shaoli Liu, Sizhe Fan, Jianhua Liu, Jia Hu, Hao Gong

“…In this paper, we propose a novel invalid point removal framework that consists of two aspects: (1) A convolutional neural network (CNN) is designed to segment the foreground from the background of different intensity conditions in FPP measurement circumstances to remove background points and the most discrete points in background regions. (2) A two-step method based on the fringe image intensity threshold and a bilateral filter is proposed to eliminate the small number of discrete points remaining after background segmentation caused by shadows and edge areas on objects. …”
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Dual Branch Encoding Feature Aggregation for Cloud and Cloud Shadow Detection of Remote Sensing Image by Naikang Shi, Haifeng Lin, Huiwen Ji, Min Xia

“…By capitalizing on their complementary strengths, this work proposed a dual-branch feature extraction architecture that utilizes two different feature aggregation modes to effectively aggregate features of CNN and Transformer at different levels. …”
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DA-Net: Dual Attention Network for Haze Removal in Remote Sensing Image by Namwon Kim, Il-Seok Choi, Seong-Soo Han, Chang-Sung Jeong

“…The previous deep learning models make use of large convolutional kernel and attention mechanisms for efficient dehazing. …”
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Real-Time Fault Diagnosis of Mooring Chain Jack Hydraulic System Based on Multi-Scale Feature Fusion Under Diverse Operating Conditions by Yujia Liu, Wenhua Li, Haoran Ye, Shanying Lin, Lei Hong

“…Under complex and dynamic marine operating conditions, different severity faults in the CJ hydraulic system display distinct time-scale characteristics. …”
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Evaluating Wind Speed Forecasting Models: A Comparative Study of CNN, DAN2, Random Forest and XGBOOST in Diverse South African Weather Conditions by Fhulufhelo Walter Mugware, Caston Sigauke, Thakhani Ravele

“…This research compares the effectiveness of Dynamic Architecture for Artificial Neural Networks (DAN2), convolutional neural networks (CNN), random forest and XGBOOST in predicting wind speed across three locations in South Africa, characterised by different weather patterns. …”
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Skin Cancer Image Classification Using Artificial Intelligence Strategies: A Systematic Review by Ricardo Vardasca, Joaquim Gabriel Mendes, Carolina Magalhaes

“…This systematic review concerns the implementation of AI methods for skin tumor classification with different imaging modalities, following the PRISMA guidelines. …”
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Artificial Intelligence for Automatic Pain Assessment: Research Methods and Perspectives by Marco Cascella, Daniela Schiavo, Arturo Cuomo, Alessandro Ottaiano, Francesco Perri, Renato Patrone, Sara Migliarelli, Elena Giovanna Bignami, Alessandro Vittori, Francesco Cutugno

“…More recently, artificial neural networks such as convolutional and recurrent neural network algorithms are implemented, even in combination. …”
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Mobile Traffic Prediction at the Edge Through Distributed and Deep Transfer Learning by Alfredo Petrella, Marco Miozzo, Paolo Dini

“…Two main Deep Learning architectures are designed based on Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) and tested under different training conditions. …”
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Multimodal Data Fusion Framework for Early Prediction of Autism Spectrum Disorder by Mohemmed Sha, Hussein Al-Dossary, Mohamudha Parveen Rahamathulla

“…Therefore, a framework was suggested to assess different deep learning models for the early identification of ASD. …”
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Fusarium Wilt of Banana Latency and Onset Detection Based on Visible/Near Infrared Spectral Technology by Cuiling Li, Dandan Xiang, Shuo Yang, Xiu Wang, Chunyu Li

“…Different data preprocessing methods were utilized, and Fisher discriminant analysis (FDA), an extreme learning machine (ELM), and a one-dimensional convolutional neural network (1D-CNN) were used to establish the classification models of the disease grades. …”
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Deep Learning to Estimate Model Biases in an Operational NWP Assimilation System by Patrick Laloyaux, Thorsten Kurth, Peter Dominik Dueben, David Hall

“…Preliminary results show that convolutional NNs are adequate to estimate model bias from RO temperature retrievals. …”
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Boosting Degradation Representation Learning for Blind Image Super-Resolution by YUAN Jiang, MA Ji, ZHOU Dengwen

“…In most convolutional neural networks-based super-resolution (SR) methods, the degradation assumptions are fixed and known (e.g., bicubic degradation). …”
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Drug-drug interaction prediction of traditional Chinese medicine based on graph attention networks by Bin Yang, Dan Song, Yadong Li, Jinglong Wang

“…Our approach leverages graph-based representations of chemical molecules and employs attention mechanism to extract deep structural features, enabling the effective prediction of TCMDDI by capturing spatial structural relationships among different compounds. Furthermore, we construct a comprehensive dataset encompassing three different categories of herbal ingredients, informed by traditional TCM principles. …”
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Multi-label Bird Species Classification Using Transfer Learning Network by Xue HAN, Jianxin PENG

“…The final dataset consists of 28 000 audio clips, each 5 s long, containing overlapping vocalizations of two or three bird species among 11 different species. Several pre-trained convolutional neural networks (CNNs), including InceptionV3, ResNet50, VGG16, and VGG19, were evaluated for extracting deep features from audio signals represented as mel spectrograms. …”
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Research on Surface Defects Classification for PET Preform by Fusing Multi-Scale Features by Chunmei Duan, Taochuan Zhang, Lei Han, Huilin Tan

“…The original image and feature map of the PET preform are respectively input into the deep convolutional neural network for feature extraction and fusion. …”
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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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Effects of Automatic Hyperparameter Tuning on the Performance of Multi‐Variate Deep Learning‐Based Rainfall Nowcasting by Amirmasoud Amini, Mehri Dolatshahi, Reza Kerachian

“…This paper combines different convolutional, long short‐term memory (LSTM)‐based networks and NWPs using ensemble techniques (i.e., bagging, random forest, and adaboost methods) with automatic hyperparameter tuning for multi‐step rainfall nowcasting. …”
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Protein sequence classification using natural language processing techniques by Huma Perveen, Julie Weeds

“…Performance was tested using different amino acid ranges and sequence lengths with a focus on generalization across unseen evolutionary families. …”
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CNN‐based off‐angle iris segmentation and recognition by Ehsaneddin Jalilian, Mahmut Karakaya, Andreas Uhl

“…In this work, the general effect of different gaze angles on ocular biometrics is discussed, and the findings are then related to the CNN‐based off‐angle iris segmentation results and the subsequent recognition performance. …”
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