DC-BiLSTM-CNN Algorithm for Sentiment Analysis of Chinese Product Reviews by Yuanfang Dong, Xiaofei Li, Meiling He, Jun Li

“…The rapid growth of e-commerce has led to a significant increase in user feedback, especially in the form of post-purchase comments on online platforms. These reviews not only reflect customer sentiments but also crucially influence other users’ purchasing decisions due to their public accessibility. …”
Get full text

Landslide Segmentation in High-Resolution Remote Sensing Images: The Van–UPerAttnSeg Framework with Multi-Scale Feature Enhancement by Chang Li, Quan Zou, Guoqing Li, Wenyang Yu

“…In addition, this study introduces a sliding window algorithm based on Gaussian fusion as a post-processing method, which optimizes the prediction of landslide edge in high-resolution remote sensing images and ensures the context reasoning ability of the model. …”
Get full text

Road Damage Detection Using YOLOv7 with Cluster Weighted Distance-IoU NMS by Rudy Rachman, Nanik Suciati, Shintami Chusnul Hidayati

“…The object detection method requires post-processing for its detection results to save only the best prediction from the method, namely, non-maximum suppression (NMS). …”
Get full text

Deep learning based rapid X-ray fluorescence signal extraction and image reconstruction for preclinical benchtop X-ray fluorescence computed tomography applications by Amrit Kaphle, Sandun Jayarathna, Sang Hyun Cho

“…Notably, the DL approach (vs. the conventional approach) reduced the total post-processing time per slice from approximately 6 min to just 1.25 s.…”
Get full text

YOLOv8m for Automated Pepper Variety Identification: Improving Accuracy with Data Augmentation by Madalena de Oliveira Barbosa, Fernanda Pereira Leite Aguiar, Suely dos Santos Sousa, Luana dos Santos Cordeiro, Irenilza de Alencar Nääs, Marcelo Tsuguio Okano

“…This research addresses the critical need for an efficient and precise identification of <i>Capsicum</i> spp. fruit varieties within the post-harvest contexts to enhance quality control and ensure consumer satisfaction. …”
Get full text

Energy saving by Artificial intelligence-based fault detection and diagnosis: 42 chiller case studies by Yen-Tang Chen, Da-Sheng Lee, Jhih-Jie Yang, Wei-Tao Huang, Yen-Po Liu

“…Among them, three faults resulted in prolonged operation post-failure, leading to abnormal energy consumption. …”
Get full text

Generation of Shape Models of Calcified TAVR populations for Solid Mechanics Simulations by means of Deep Learning by Oldenburg Jan, Borowski Finja, Supp Laura, Öner Alper, Schmitz Klaus-Peter, Stiehm Michael

“…A critical aspect of advancing TAVR procedures lies in preoperative planning, integrating patient-specific in-silico deployment simulation and post-deployment fluid mechanics assessments. This study introduces a novel approach to calcified TAVR patient shape modeling, addressing this problems. …”
Get full text

An adaptive deep learning approach based on InBNFus and CNNDen-GRU networks for breast cancer and maternal fetal classification using ultrasound images by Mamuna Fatima, Muhammad Attique Khan, Anwar M. Mirza, Jungpil Shin, Areej Alasiry, Mehrez Marzougui, Jaehyuk Cha, Byoungchol Chang

“…Abstract Convolutional Neural Networks (CNNs), a sophisticated deep learning technique, have proven highly effective in identifying and classifying abnormalities related to various diseases. …”
Get full text

A Violet‐Light‐Responsive ReRAM Based on Zn2SnO4/Ga2O3 Heterojunction as an Artificial Synapse for Visual Sensory and In‐Memory Computing by Saransh Shrivastava, Wei‐Sin Dai, Stephen Ekaputra Limantoro, Hans Juliano, Tseung‐Yuen Tseng

“…Classification of three‐channeled images corrupted with different levels (0.15–0.9) of Gaussian noise is achieved by simulating a convolutional neural network (CNN). The violet light (405 nm) illumination generates excitatory post synaptic current (EPSC), which is influenced by the persistent photoconductivity (PPC) effect after discontinuing the optical excitation. …”
Get full text

Developing a multi-variate prediction model for COVID-19 from crowd-sourced respiratory voice data by Yuyang Yan, Wafaa Aljbawi, Sami O. Simons, Visara Urovi

“…Aim: COVID-19 has affected more than 223 countries worldwide and in the post-COVID era, there is a pressing need for non-invasive, low-cost, and highly scalable solutions to detect COVID-19. …”
Get full text

A deep learning based multiple RNA methylation sites prediction across species by Sajid Shah, Saima Jabeen, Mohammed ElAffendi, Ishrat Khan, Muhammad Almas Anjum, Mohamed A. Bahloul

“…Methylation of ribonucleic acid (RNA) is an essential post-transcriptional alteration that has a major effect on many biological processes. …”
Get full text

MolNexTR: a generalized deep learning model for molecular image recognition by Yufan Chen, Ching Ting Leung, Yong Huang, Jianwei Sun, Hao Chen, Hanyu Gao

“…We further incorporate a series of advanced algorithms, including an improved data augmentation module, an image contamination module, and a post-processing module for getting the final SMILES output. …”
Get full text

FD-YOLO: A YOLO Network Optimized for Fall Detection by Hoseong Hwang, Donghyun Kim, Hochul Kim

“…First, a global attention module (GAM) based on the Convolutional Block Attention Module (CBAM) was employed to improve detection performance. …”
Get full text

Enhanced YOLOv8 for Robust Pig Detection and Counting in Complex Agricultural Environments by Jian Li, Wenkai Ma, Yanan Wei, Tan Wang

“…These improvements include DCNv4 deformable convolutions for irregular pig postures, BiFPN bidirectional feature fusion for multi-scale information integration, EfficientViT linear attention for computational efficiency, and PIoU v2 loss for improved overlap handling. (2) A density-aware post-processing module with intelligent NMS strategies that adapt to different crowding scenarios. …”
Get full text

Ensemble Machine Learning, Deep Learning, and Time Series Forecasting: Improving Prediction Accuracy for Hourly Concentrations of Ambient Air Pollutants by Valentino Petrić, Hussain Hussain, Kristina Časni, Milana Vuckovic, Andreas Schopper, Željka Ujević Andrijić, Simonas Kecorius, Leizel Madueno, Roman Kern, Mario Lovrić

“…The utilisation of surface atmospheric ERA5-Land datasets within the models as model features showed high feature post hoc importance in the best (hybrid) models per pollutant and site. …”
Get full text

YOLO-SAG: An improved wildlife object detection algorithm based on YOLOv8n by Lingli Chen, Gang Li, Shunkai Zhang, Wenjie Mao, Mei Zhang

“…Integrating the GSConv and VoV-GSCSP module lightens neck convolutions, reducing computational redundancy and balancing the computational and parametric quantities brought by the AIFI. …”
Get full text

Task-Driven Real-World Super-Resolution of Document Scans by Maciej Zyrek, Tomasz Tarasiewicz, Jakub Sadel, Aleksandra Krzywon, Michal Kawulok

“…These improvements are statistically significant as confirmed by the Kruskal–Wallis H test and the post hoc Dunn test with Benjamini–Hochberg <i>p</i>-value correction. …”
Get full text

Enhancing chronic wound assessment through agreement analysis and tissue segmentation by Ana C. Morgado, Rafaela Carvalho, Ana Filipa Sampaio, Maria J. M. Vasconcelos

“…The results show the benefits of employing previous knowledge gained from simpler tasks within the same domain, as well as the efficacy of post-processing operations. The top-performing tissue segmentation model, DeepLabV3-R50, achieved an overall mean Intersection over Union of 62.95% and a mean Dice score of 76.82% for the three analysed tissues on the Wounds dataset, when assessed independently. …”
Get full text

AI-Based Forecasting in Renewable-Rich Microgrids: Challenges and Comparative Insights by Martins Osifeko, Josiah Lange Munda

“…Classical ML models outperformed most DL architectures, including Transformer and Convolutional Neural Network (CNN)-LSTM, which underperformed despite their complexity. …”
Get full text

A Deep Learning Framework for Chronic Kidney Disease stage classification by Gayathri Hegde M, P Deepa Shenoy, Venugopal KR, Arvind Canchi

“…Statistical tests, including the Friedman and Nemenyi post-hoc test, identified the CNN model trained with MHMXAI-selected features as the most robust choice for CKD stage prediction. …”
Get full text