Enhancing Speaker Recognition with CRET Model: a fusion of CONV2D, RESNET and ECAPA-TDNN by Pinyan Li, Lap Man Hoi, Yapeng Wang, Xu Yang, Sio Kei Im

“…Abstract In today’s society, speaker recognition plays an increasingly important role. Currently, neural networks are widely employed for extracting speaker features. …”
Get full text

Machine Learning-Based Weld Classification for Quality Monitoring by Rojan Ghimire, Rajiv Selvam

“…In this research project, a deep learning approach is proposed to classify weld defects using convolutional neural networks (CNNs) to automate the process. …”
Get full text

Machine Learning and Deep Learning for Wildfire Spread Prediction: A Review by Henintsoa S. Andrianarivony, Moulay A. Akhloufi

“…In contrast, DL approaches, such as convolutional neural networks (CNNs) and convolutional recurrent networks (CRNs), excel at handling the spatiotemporal complexities of wildfire data. …”
Get full text

AS-Faster-RCNN: An Improved Object Detection Algorithm for Airport Scene Based on Faster R-CNN by Zhige He, Yuanqing He

“…Secondly, The DCN (Deformable Convolution Network) is employed in the backbone to strengthen the ability of extracting features for deformed objects. …”
Get full text

Evaluating the efficacy and site-specific performance of machine learning approaches: A comprehensive review of autism detection models by Deblina Mazumder Setu, Tania Islam, Md Maklachur Rahman, Samrat Kumar Dey, Tazizur Rahman

“…And four of them are more progressive, sophisticated methods including the convolutional neural network (CNN) model, diagnostic autism spectrum disorder (DASD) strategy, Ensemble Diagnosis Methodology (EKNN), and Self-Organizing Maps (SOM). …”
Get full text

Infilling of missing rainfall radar data with a memory-assisted deep learning approach by J. Meuer, L. M. Bouwer, L. M. Bouwer, F. Kaspar, R. Lehmann, W. Karl, T. Ludwig, C. Kadow

“…We propose a deep convolutional neural network enhanced with a memory component to better account for temporal changes in precipitation fields. …”
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

Educational Psychology Analysis Method for Extracting Students’ Facial Information Based on Image Big Data by Maoyue Zhang

“…At present, most of the research on academic emotions focuses on the concept, current situation, and relevance. There are not many researches on the application of artificial intelligence-based neural network facial expression recognition technology in practical teaching. …”
Get full text

A Motion‐Sensing Integrated Soft Robot with Triboelectric Nanogenerator for Pipeline Inspection by Rui Chen, Huigang Wang, Haoji Wang, Huijiang Wang, Li Bai, Xinpei Ai, Lifu Liu, Zhihao Hu, Zean Yuan

“…The T‐TENG‐based sensory system outputs distinct voltage signals upon exposed to different material and structural conditions, for which a 1D‐convolutional neutral network algorithm is exposed to process with the sequential signals. …”
Get full text

Recent Advancement in Small Traffic Sign Detection: Approaches and Dataset by R. Suresha, N. Manohar, G. Ajay Kumar, M. Rohit Singh

“…This review comprehensively examines the performance of state-of-the-art deep learning models, including YOLO (You Only Look Once), SSD (Single Shot MultiBox Detector), and various RCNN (Region-based Convolutional Neural Network) variants, assessing their strengths and weaknesses for small traffic sign detection through detailed tables and bar graphs. …”
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

“…In this work, inter-rater agreement analyses were conducted to evaluate the consistency of manual annotations performed by multiple experts and an automated methodology for tissue segmentation leveraging advanced deep learning techniques is proposed. For this, the convolutional neural network DeepLabV3-R50 and a transformer-based approach (SegFormer-B0) were explored. …”
Get full text

Research on a Joint Extraction Method of Track Circuit Entities and Relations Integrating Global Pointer and Tensor Learning by Yanrui Chen, Guangwu Chen, Peng Li

“…First, a multi-layer dilate gated convolutional neural network with residual connections is used to extract key features and fuse the weighted information from the 12 different semantic layers of the RoBERTa-wwm-ext model, fully exploiting the performance of each encoding layer. …”
Get full text

Unmanned Aerial Vehicle-Based Hyperspectral Imaging for Potato Virus Y Detection: Machine Learning Insights by Siddat B. Nesar, Paul W. Nugent, Nina K. Zidack, Bradley M. Whitaker

“…The performance of the models is promising, with the convolutional neural network (CNN) achieving a recall of 0.831, reliably identifying the PVY-infected plants. …”
Get full text

Construction and scheduling optimization of renewable energy consumption forecasting system for twisted tire porcelain manufacturing industry based on deep learning by Fangrong Liao, Runlin Ran, Jiayi Zhang

“…At the same time, based on the convolutional neural network model Alexnet, the cross-entropy loss function is selected as the training loss, and the twisted tire porcelain pattern classification algorithm under the deep learning framework is designed. …”
Get full text

Abnormality detection in nailfold capillary images using deep learning with EfficientNet and cascade transfer learning by Mona Ebadi Jalal, Omar S. Emam, Cristián Castillo-Olea, Begoña García-Zapirain, Adel Elmaghraby

“…Our proposed model achieved superior performance, with accuracy, precision, recall, F1 score, and ROC_AUC of 1.00, significantly outperforming both models of single transfer learning on the pre-trained EfficientNet-B0 and cascade transfer learning on a convolutional neural network, which each attained an accuracy, precision, recall, and F1 score of 0.67 and a ROC_AUC of 0.83. …”
Get full text

UNestFormer: Enhancing Decoders and Skip Connections With Nested Transformers for Medical Image Segmentation by Adnan Md Tayeb, Tae-Hyong Kim

“…Precise identification of organs and lesions in medical images is essential for accurate disease diagnosis and analysis of organ structures. Deep convolutional neural network (CNN)-based U-shaped networks are among the most popular and promising approaches for this task. …”
Get full text

Design of a Portable Biofeedback System for Monitoring Femoral Load During Partial Weight-Bearing Walking by Tao Ma, Tianyang Fan, Xun Xu, Tao Sun

“…Utilizing data collected from 12 participants, a physics-informed temporal convolutional network (PITCN) method was proposed to estimate the internal femoral loading. …”
Get full text

Development of an Augmented Reality Surgical Trainer for Minimally Invasive Pancreatic Surgery by Doina Pisla, Nadim Al Hajjar, Gabriela Rus, Bogdan Gherman, Andra Ciocan, Corina Radu, Calin Vaida, Damien Chablat

“…Using Unity and the HoloLens 2, the simulator offers a realistic augmented environment, enhancing spatial awareness and planning in surgical scenarios. A convolutional neural network (CNN) model predicts forces without physical sensors, achieving a mean absolute error of 0.0244 N. …”
Get full text

Advancements in Herpes Zoster Diagnosis, Treatment, and Management: Systematic Review of Artificial Intelligence Applications by Dasheng Wu, Na Liu, Rui Ma, Peilong Wu

“…Classification tasks (85.2%) dominated AI applications, with neural networks, particularly multilayer perceptron and convolutional neural networks being the most frequently used algorithms. …”
Get full text

High-precision segmentation and quantification of tunnel lining crack using an improved DeepLabV3+ by Zhutian Pan, Xuepeng Zhang, Yujing Jiang, Bo Li, Naser Golsanami, Hang Su, Yue Cai

“…The proposed EDeepLab outperforms other models including U-Net, ResNet and fully convolutional networks in the quantitative analysis of tiny cracks and noise interference.…”
Get full text