CCDR: Combining Channel-Wise Convolutional Local Perception, Detachable Self-Attention, and a Residual Feedforward Network for PolSAR Image Classification by Jianlong Wang, Bingjie Zhang, Zhaozhao Xu, Haifeng Sima, Junding Sun

“…This article proposes a novel method for PolSAR image classification that combines channel-wise convolutional local perception, detachable self-attention, and a residual feedforward network. …”
Get full text

Research on Android malware detection method based on multimodal feature fusion by Ge Jike, He Mingkun, Chen Zuqin, Ling Jin, Zhang Yifan

Subjects: Get full text

A feedforward mechanism for human-like contour integration. by Fenil R Doshi, Talia Konkle, George A Alvarez

“…Here, we demonstrate that feedforward convolutional neural networks (CNNs) fine-tuned on contour detection show this human-like capacity, but without relying on mechanisms proposed in prior work, such as lateral connections, recurrence, or top-down feedback. …”
Get full text

Human activity recognition algorithms for manual material handling activities by Andreas Sochopoulos, Tommaso Poliero, Jamil Ahmad, Darwin G. Caldwell, Christian Di Natali

Subjects: Get full text

MambaPose: A Human Pose Estimation Based on Gated Feedforward Network and Mamba by Jianqiang Zhang, Jing Hou, Qiusheng He, Zhengwei Yuan, Hao Xue

Get full text

Spectral-Spatial Convolutional Hybrid Transformer for Hyperspectral Image Classification by Haixin Sun, Jingwen Xu, Fanlei Meng, Mengdi Cheng, Qiuguang Cao

“…First, the spectral pyramid 3D convolution and 2D convolution are combined to extract joint and detailed spectral-spatial features. …”
Get full text

Numerical Estimation of Bending in Holographic Volume Gratings by Means of RCWA and Deep Learning by Jaume Colomina-Martínez, Juan Carlos Bravo, Joan Josep Sirvent-Verdú, Adrián Moya-Aliaga, Jorge Francés, Cristian Neipp, Augusto Beléndez

Subjects: Get full text

Highway Traffic Flow Prediction Algorithm Based on Multiscale Transformation and Convolutional Networks by Yuzhu Luo, Jiarong Wang, Ming Wei

“…In order to solve the problem that the traditional long-term high-speed traffic forecasting algorithm is affected by the approximation ability of the function and easy to fall into the local mass value, we wrote a multivariate-based highway traffic forecasting algorithm scaling and convolutional networks. Because the feedforward wavelet neural network algorithm predicts the short-term traffic flow in different areas, it is necessary to examine the ability to predict the difference between different models. …”
Get full text

Advanced Hydro-Informatic Modeling Through Feedforward Neural Network, Federated Learning, and Explainable AI for Enhancing Flood Prediction by Shahariar Hossain Mahir, Md Tanjum An Tashrif, Md Ahsan Karim, Dipanjali Kundu, Anichur Rahman, Md. Amir Hamza, Fahmid Al Farid, Abu Saleh Musa Miah, Sarina Mansor

Get full text

Convolutional Neural Network for the Classification of the Control Mode of Grid-Connected Power Converters by Rabah Ouali, Martin Legry, Jean-Yves Dieulot, Pascal Yim, Xavier Guillaud, Frédéric Colas

“…This paper introduces a novel classification algorithm based on Convolutional Neural Networks (CNN), capable of detecting patterns in sequential data. …”
Get full text

DTCformer: A Temporal Convolution-Enhanced Autoformer with DILATE Loss for Photovoltaic Power Forecasting by Quanhui Qiu, Dejun Ning, Qiang Guo, Jiang Wei, Huichang Chen, Lihui Sui, Yi Liu, Zibing Du, Shipeng Liu

“…The proposed model integrates a Temporal Convolution Feedforward Network module and a Variable Selection Embedding module, effectively capturing inter-variable dependencies and temporal periodicity. …”
Get full text

Object-based feedback attention in convolutional neural networks improves tumour detection in digital pathology by Andrew Broad, Alexander Wright, Clare McGenity, Darren Treanor, Marc de Kamps

“…We demonstrate that at the end of the saccade sequence the system has an improved classification ability compared to the convolutional neural network (CNN) that represents the feedforward part of the model. …”
Get full text

Temporal fusion strategy for violence detection: utilising convolutional and LSTM neural networks for surveillance videos by Khaled Merit, Mohammed Beladgham, Abdelmalik Taleb-Ahmed

“…This paper introduces sophisticated models using Convolutional Neural Networks (CNN), specifically MobileNet V3, VGG16, and InceptionV3 networks, as well as networks using LSTM and feedforward networks. …”
Get full text

Comparison of discrete transforms for deep‐neural‐networks‐based speech enhancement by Wissam A. Jassim, Naomi Harte

Get full text

Transformer network enhanced by dual convolutional neural network and cross-attention for wheelset bearing fault diagnosis by Jing Zhao, Jing Zhao, Junfeng Li, Ziteng Li, Zengqiang Ma, Zengqiang Ma

“…To address these challenges, this study proposes a Transformer network model based on dual convolutional neural networks and cross-attention enhancement (Trans-DCC) for wheelset bearing fault diagnosis. …”
Get full text

On the Integration of Social Context for Enhanced Fake News Detection Using Multimodal Fusion Attention Mechanism by Hachemi Nabil Dellys, Halima Mokeddem, Layth Sliman

Subjects: Get full text

CMDMamba: dual-layer Mamba architecture with dual convolutional feed-forward networks for efficient financial time series forecasting by Zhenkai Qin, Zhenkai Qin, Zhenkai Qin, Baozhong Wei, Baozhong Wei, Yujia Zhai, Ziqian Lin, Xiaochuan Yu, Xiaochuan Yu, Jingxuan Jiang

“…The CMDMamba model employs a dual-layer Mamba structure that effectively captures price fluctuations at both the micro- and macrolevels in financial markets and integrates an innovative Dual Convolutional Feedforward Network (DconvFFN) module. …”
Get full text

Comparative analysis of convolutional neural networks and traditional machine learning models for IVF live birth prediction: a retrospective analysis of 48514 IVF cycles and an eva... by Yu Liu, Yi Wang, Kai Huang, Hao Shi, Hang Xin, Shanjun Dai, Jinhao Liu, Xinhong Yang, Jianyuan Song, Fuli Zhang, Yihong Guo

“…Its performance was comparable to Random Forest (accuracy: 0.9406 ± 0.0017, AUC: 0.9734 ± 0.0012), and superior to Decision Tree, Naïve Bayes, and Feedforward Neural Network in recall and robustness. …”
Get full text

Seismic data denoising based on attention dual dilated CNN by Haixia Hu, Youhua Wei, Hui Chen, Xingan Fu, Ji Zhang, Quan Wang, Shiwei Cai

“…Experimental results show that ADDC-Net outperforms feedforward DnCNN and DudeNet, improving PSNR by 2.8905 dB and 0.6410 dB, respectively. …”
Get full text

BAM-SLDK: biologically inspired attention mechanism with spiking learnable delayed kernel synapses by Mario Chacón-Falcón, Alberto Patiño-Saucedo, Luis Camuñas-Mesa, Teresa Serrano-Gotarredona, Bernabé Linares-Barranco

“…However, in order to effectively process data with rich spatial and temporal dependencies, the usual static projections (feedforward and recurrent) among layers of spiking neurons fail to represent all the information needed. …”
Get full text