Posture Monitoring of Patients in Radiotherapy Scenarios Based on Stacked Grayscale 3-Channel Images by Yang Zhang, Ziwen Wei, Zhihua Liu, Xiaolong Wu, Junchao Qian

“…This approach enabled capturing motion information through a large-scale dataset pre-trained 2D convolutional neural network (CNN), eliminating the need for computationally expensive optical flow calculations. …”
Get full text

The Application of a Marine Weather Data Reconstruction Model Based on Deep Super-Resolution in Ship Route Optimization by Shangfu Li, Junfu Yuan, Zhizheng Wu

“…Firstly, the model uses a convolutional neural network to extract features from wind speed and wave height data. …”
Get full text

DeepLASD countermeasure for logical access audio spoofing by Hamed Al-Tairi, Ali Javed, Tasawer Khan, Abdul Khader Jilani Saudagar

“…The model incorporates a SincConv layer for interpretable spectral processing, along with residual convolutional blocks that integrate attention for improved feature extraction. …”
Get full text

Recent Trends and Advances in Utilizing Digital Image Processing for Crop Nitrogen Management by Bhashitha Konara, Manokararajah Krishnapillai, Lakshman Galagedara

“…Interest in integrating machine learning and deep learning algorithms with DIP has increased, with the frequently used algorithms—Random Forest, Support Vector Machine, Extreme Gradient Boost, and Convolutional Neural Networks—achieving higher prediction accuracy levels. …”
Get full text

Intelligent Hybrid SHM-NDT Approach for Structural Assessment of Metal Components by Romaine Byfield, Ahmed Shabaka, Milton Molina Vargas, Ibrahim Tansel

“…In contrast, SHM employs permanently installed, cost-effective sensors to enable continuous monitoring, though often with reduced detail. …”
Get full text

Amazonian manatee critical habitat revealed by artificial intelligence‐based passive acoustic techniques by Florence Erbs, Mike van derSchaar, Miriam Marmontel, Marina Gaona, Emiliano Ramalho, Michel André

“…Passive acoustics can cost‐effectively acquire terrestrial and underwater long‐term data. …”
Get full text

Durability prediction of sustainable marine concrete under freeze-thaw cycles using multi-objective machine learning models by Aïssa Rezzoug, Ali H. AlAteah, Sadiq Alinsaif, Sahar A. Mostafa

“…Four machine learning techniques were utilized: a convolutional neural network (CNN), a genetic algorithm with optimized artificial neural network (GA-ANN), an adaptive neuro-fuzzy inference system (ANFIS), and multi-objective optimization (MOO). …”
Get full text

A Latent Multi-Scale Residual Transformer Approach for Cross-Modal Medical Image Synthesis by Xinmiao Zhu, Yang Li

“…Existing approaches predominantly utilize convolutional neural networks (CNNs) or vision transformers (ViTs) and their variants as model backbones. …”
Get full text

Study of Cathode Materials for Na-Ion Batteries: Comparison Between Machine Learning Predictions and Density Functional Theory Calculations by Claudio Ronchetti, Sara Marchio, Francesco Buonocore, Simone Giusepponi, Sergio Ferlito, Massimo Celino

“…The limitations associated with lithium’s supply chain, cost, and safety concerns have prompted the exploration of alternative battery chemistries. …”
Get full text

ECGConVT: A Hybrid CNN and Vision Transformer Model for Enhanced 12-Lead ECG Images Classification by Mudassar Khalid, Charnchai Pluempitiwiriyawej, Abdulkadhem A. Abdulkadhem, Imran Afzal, Tien Truong

“…We propose ECGConVT framework that combines Convolutional Neural Network (CNN) module for extracting local features, and Vision Transformer (ViT) module for capturing global features. …”
Get full text

MDRN: Multi-distillation residual network for efficient MR image super-resolution by Liwei Deng, Jingyi Chen, Xin Yang, Sijuan Huang

“…However, current SR methods often use the complex convolutional network for feature extraction, which is difficult to train and not suitable for limited computation resources in the medical scenario. …”
Get full text

Fungi-Kcr: a language model for predicting lysine crotonylation in pathogenic fungal proteins by Yong-Zi Chen, Yong-Zi Chen, Xiaofeng Wang, Zhuo-Zhi Wang, Haixin Li, Haixin Li

“…The model integrates convolutional neural networks (CNN), gated recurrent units (GRU), and word embedding to effectively capture both local and long-range sequence dependencies.ResultsComprehensive evaluations, including ten-fold cross-validation and independent testing, demonstrate that Fungi-Kcr achieves superior predictive performance compared to conventional machine learning models. …”
Get full text

NRNH-AR: A Small Robotic Agent Using Tri-Fold Learning for Navigation and Obstacle Avoidance by Carlos Vasquez-Jalpa, Mariko Nakano, Martin Velasco-Villa, Osvaldo Lopez-Garcia

“…The proposed algorithm was evaluated in four critical aspects: computational cost, learning stability, required memory size, and operation speed. …”
Get full text

Artificial intelligence and Artificial Neural Networks in toxicology: challenges, perspectives and applications (Narrative review) by Sara Karimi ZEVERDEGANI, Elham SABER, Samira BARAKAT

“…Regularized and fully connected convolutional neural networks cannot detect and detect discrete changes in toxicity related two-dimensional data patterns. …”
Get full text

Redefining failure detection in PV Systems: a comparative study of GPT-4o and ResNet's computer vision in aerial infrared imagery analysis by Gallmetzer Sandra, Sondoqah Mousa, Turri Evelyn, Koester Lukas, Louwen Atse, Moser David

“…This study investigates the application of advanced artificial intelligence methods for fault detection and classification comparing the performance of GPT-4o, a multimodal large language model, and ResNet, a convolutional neural network renowned for image classification tasks. …”
Get full text

Citrus Disease Classification Model Based on Improved ConvNeXt by Jichi Yan, Yongbin Mo, Yannan Yu, Shiqing Dou, Rongfeng Yang

“…Early diagnosis of citrus diseases directly affects the yield and quality of citrus cultivation, and a citrus disease classification model based on improved ConvNeXt is proposed to address the problems of high cost and low efficiency of traditional citrus disease detection methods. …”
Get full text

Research and Application of Structural Plane Identification for Roadway Surrounding Based on Deep Learning by Qiang Xu, Ze Xia, Gang Huang, Xuehua Li, Xu Gao, Yukuan Fan

“…Second, a deep Coral architecture based on a convolutional neural network (CNN) was established to automatically extract features from the borehole images and classify the structural planes therein. …”
Get full text

Temperature Prediction and Fault Warning of High-Speed Shaft of Wind Turbine Gearbox Based on Hybrid Deep Learning Model by Min Zhang, Jijie Wei, Zhenli Sui, Kun Xu, Wenyong Yuan

“…Compared to the long short-term memory (LSTM) and convolutional neural network and LSTM hybrid models, the STA architecture reduces the root mean square error of the prediction by approximately 37% and 13%, respectively. …”
Get full text

MultiFG: integrating molecular fingerprints and graph embeddings via attention mechanisms for robust drug side effect prediction by Zuhai Hu, Jinxiang Yang, Linghao Ni, Liyuan Zhang, Bin Peng

“…Abstract Accurate prediction of drug side effect frequencies is critical for drug safety assessment but remains challenging due to the high cost of clinical trials and the limited generalizability of existing models. …”
Get full text

MemoCMT: multimodal emotion recognition using cross-modal transformer-based feature fusion by Mustaqeem Khan, Phuong-Nam Tran, Nhat Truong Pham, Abdulmotaleb El Saddik, Alice Othmani

“…However, these models come at a computational cost. In contrast, convolutional neural networks are faster but struggle with capturing these long-range relationships. …”
Get full text