RACNet: risk assessment Net of cervical lesions in colposcopic images by Tianxiang Xu, Peizhong Liu, Ping Li, Xiaoxia Wang, Huifeng Xue, JingMing Guo, Binhua Dong, Pengming Sun

“…Then, these lesions are classified by designing a multi-branch convolutional neural network (CNN) to improve the performance of risk assessment. …”
Get full text

Models, systems, networks in economics, engineering, nature and society by L.Yu. Кrivonogov1, S.F. Levin, I.S. Inomboev, D.V. Papshev

“…The aim of the study is to create and evaluate a convolutional neural network model for automatic ECG signals classification in 12 standard leads to identify the most common and dangerous cardiovascular diseases. …”

Vision-Based UAV Localization on Various Viewpoints by Yee-Ming Ooi, Che-Cheng Chang, Yu-Min Su, Chiao-Ming Chang

“…In the literature, an existing vision-based study is proposed to position the drone by a shallow Convolutional Neural Network (CNN). However, they only consider a constant viewpoint (towards the north). …”
Get full text

Knowledge graph-based entity alignment with unified representation for auditing by Youhua Zhou, Xueming Yan, Han Huang, Zhifeng Hao, Haofeng Zhu, Fangqing Liu

“…Our proposed KG-Marfia first extracts entity representations by addressing the imbalance of attributes and relations, and then designs a stacked graph convolutional network as an encoder to fuse attribute and relation information, learning unified representations for entities. …”
Get full text

Detecting Phishing URLs Based on a Deep Learning Approach to Prevent Cyber-Attacks by Qazi Emad ul Haq, Muhammad Hamza Faheem, Iftikhar Ahmad

“…Phishing is one of the most widely observed types of internet cyber-attack, through which hundreds of clients using different internet services are targeted every day through different replicated websites. …”
Get full text

Ada-GCNLSTM: An adaptive urban crime spatiotemporal prediction model by Miaoxuan Shan, Chunlin Ye, Peng Chen, Shufan Peng

“…While many effective spatiotemporal crime prediction methods have been proposed, most overlook this issue, reducing their ability to generalize. …”
Get full text

Nonlinear multi-head cross-attention network and programmable gradient information for gaze estimation by Yujie Li, Yuhang Hong, Ziwen Wang, Jiahui Chen, Rongjie Liu, Shuxue Ding, Benying Tan

“…Recent gaze estimation methods are primarily based on convolutional neural networks (CNNs) or attention Transformers. …”
Get full text

MobileNet-HeX: Heterogeneous Ensemble of MobileNet eXperts for Efficient and Scalable Vision Model Optimization by Emmanuel Pintelas, Ioannis E. Livieris, Vasilis Tampakas, Panagiotis Pintelas

Get full text

Simultaneous single image super‐resolution and blind Gaussian denoising via slim ghost full‐frequency residual blocks by Saghar Farhangfar, Aryaz Baradarani, Mohammad Asadpour, Mohammad Ali Balafar, Roman Gr. Maev

“…Abstract Given that super‐resolution (SR) aims to recover lost information, and low‐resolution (LR) images in real‐world conditions might be corrupted with multiple degradations, considering basic bicubic down‐sampling as the sole degradation significantly limits the performance of most existing SR models. This paper presents a model for simultaneous super‐resolution and blind additive white Gaussian noise (AWGN) denoising with two components (netdeg and netSR) that is based on a generative adversarial network (GAN) to achieve detailed results. netdeg, featuring residual and innovative cost‐effective ghost residual blocks with a frequency separation module for obtaining long‐range information, blindly restores a clean version of the LR image. netSR leverages slim ghost full‐frequency residual blocks to process low‐frequency (LF) and high‐frequency (HF) information via static large convolutions and pixel‐wise highlighted input‐adaptive dynamic convolutions, respectively. …”
Get full text

Skin Cancer Cell Detection using Image Processing by Taskin Sabit, Faiza Tasnim, Sadia Afrin Sara, Sharia Tasnim Adrita, Maisha Tarannum

“…Early diagnosis and precise detection of skin cancer represent a global health priority since this disease remains highly dangerous while being among the most frequent ones. This research investigates the effectiveness of deep learning techniques, specifically Convolutional Neural Networks (CNN) and the VGG16 architecture, for skin cancer detection and classification. …”
Get full text

HLQ: Hardware-Friendly Logarithmic Quantization Aware Training for Power-Efficient Low-Precision CNN Models by Dahun Choi, Juntae Park, Hyun Kim

“…Unlike the existing linear quantization, logarithmic quantization has the advantage that the multiply-accumulate (MAC) operation in the convolution (CONV) operation, which occupies most of the CNNs, can be replaced with the addition operation and is suitable for low-precision quantization. …”
Get full text

EfficientNet-B0 outperforms other CNNs in image-based five-class embryo grading: a comparative analysis by Vincent Jaehyun Shim, Hosup Shim, Sangho Roh

“…Methods: We evaluated the performance of five convolutional neural network architectures—EfficientNet-B0, InceptionV3, ResNet18, ResNet50, and VGG16— in grading blastocysts into five quality classes using only embryo images, without incorporating clinical or patient data. …”
Get full text

Classification and Physical Characteristic Analysis of Fermi-GBM Gamma-Ray Bursts Based on Deep Learning by Jia-Ming Chen, Ke-Rui Zhu, Zhao-Yang Peng, Li Zhang

“…We propose a new classification method based on convolutional neural networks and adopt a sample including 3774 GRBs observed by Fermi-GBM to address the T _90 overlap problem. …”
Get full text

A colonic polyps detection algorithm based on an improved YOLOv5s by Jianjun Li, Jinhui Zhao, Yifan Wang, Jinhui Zhu, Yanhong Wei, Junjiang Zhu, Xiaolu Li, Shubin Yan, Qichun Zhang

Get full text

A New Way to Identify Mastitis in Cows Using Artificial Intelligence by Rodes Angelo Batista da Silva, Héliton Pandorfi, Filipe Rolim Cordeiro, Rodrigo Gabriel Ferreira Soares, Victor Wanderley Costa de Medeiros, Gledson Luiz Pontes de Almeida, José Antonio Delfino Barbosa Filho, Gabriel Thales Barboza Marinho, Marcos Vinícius da Silva

Get full text

Predictive and Explainable Artificial Intelligence for Weight Loss After Sleeve Gastrectomy: Insights from Wide and Deep Learning with Medical Image and Non-Image Data by Jaechan Park, Sungsoo Park, Kwang-Sig Lee, Yeongkeun Kwon

“…Here, the WAD model combined a convolutional neural network (CNN) for image data and a linear layer for non-image data (EMR). …”
Get full text

Advancing Breast Cancer Detection: SE-Conformer Framework for Malignancy Detection in Histopathology Images by Lekha S. Nair, K. R. Amarnath, Jyothisha J. Nair

“…Globally, breast cancer is the second most lethal form of cancer among women, and has high rates of incidence and mortality. …”
Get full text

Bearing fault diagnosis method based on dual-channel feature fusion by ZHANG Xiaoning, ZHU Huilong, XIN Liang, YANG Muchen, WANG Hao

“…Intelligent diagnosis method based on convolution neural network (CNN) has been widely used in bearing fault diagnosis. …”
Get full text

An enhanced pattern detection and segmentation of brain tumors in MRI images using deep learning technique by Lubna Kiran, Asim Zeb, Qazi Nida Ur Rehman, Taj Rahman, Muhammad Shehzad Khan, Shafiq Ahmad, Muhammad Irfan, Muhammad Naeem, Shamsul Huda, Haitham Mahmoud

“…We introduce a cutting-edge deep-learning approach employing a binary convolutional neural network (BCNN) to address this. …”
Get full text

LeafDPN: An Improved DPN Model for the Identification of Bacterial Blight in Soybean in Natural Environments by Rui Cong, Ying Xu, Hao Su, Jiaying Zhou, Yuxi Hu, Dawei Xin, Qingshan Chen, Rongsheng Zhu, Shuang Song

Get full text