Convolutional Neural Network
Convolutional Neural Networks (CNNs) are a class of deep learning models designed for processing grid-like data, excelling in image analysis and related tasks. Current research focuses on improving CNN efficiency and robustness, exploring architectures like EfficientNet and Swin Transformers, as well as novel approaches such as Mamba models to address limitations in computational cost and long-range dependency capture. This active field of research has significant implications across diverse applications, including medical image analysis (e.g., cancer detection, Alzheimer's diagnosis), damage assessment, and art forgery detection, demonstrating the power of CNNs for automating complex visual tasks.
Papers
What Does It Mean to Be a Transformer? Insights from a Theoretical Hessian Analysis
Weronika Ormaniec, Felix Dangel, Sidak Pal Singh
LKASeg:Remote-Sensing Image Semantic Segmentation with Large Kernel Attention and Full-Scale Skip Connections
Xuezhi Xiang, Yibo Ning, Lei Zhang, Denis Ombati, Himaloy Himu, Xiantong Zhen
QIANets: Quantum-Integrated Adaptive Networks for Reduced Latency and Improved Inference Times in CNN Models
Zhumazhan Balapanov, Vanessa Matvei, Olivia Holmberg, Edward Magongo, Jonathan Pei, Kevin Zhu
MOZART: Ensembling Approach for COVID-19 Detection using Chest X-Ray Imagery
Mohammed Shabo, Nazar Siddig
Quantum-Trained Convolutional Neural Network for Deepfake Audio Detection
Chu-Hsuan Abraham Lin, Chen-Yu Liu, Samuel Yen-Chi Chen, Kuan-Cheng Chen
Learning Algorithms Made Simple
Noorbakhsh Amiri Golilarz, Elias Hossain, Abdoljalil Addeh, Keyan Alexander Rahimi
Efficient Hyperparameter Importance Assessment for CNNs
Ruinan Wang, Ian Nabney, Mohammad Golbabaee
GPR Full-Waveform Inversion through Adaptive Filtering of Model Parameters and Gradients Using CNN
Peng Jiang, Kun Wang, Jiaxing Wang, Zeliang Feng, Shengjie Qiao, Runhuai Deng, Fengkai Zhang
Deeper Insights into Deep Graph Convolutional Networks: Stability and Generalization
Guangrui Yang, Ming Li, Han Feng, Xiaosheng Zhuang
Music Genre Classification using Large Language Models
Mohamed El Amine Meguenani, Alceu de Souza Britto Jr., Alessandro Lameiras Koerich
Benign Overfitting in Single-Head Attention
Roey Magen, Shuning Shang, Zhiwei Xu, Spencer Frei, Wei Hu, Gal Vardi
Explainability of Deep Neural Networks for Brain Tumor Detection
S.Park, J.Kim
Uncertainty estimation via ensembles of deep learning models and dropout layers for seismic traces
Giovanni Messuti, ortensia Amoroso, Ferdinando Napolitano, Mariarosaria Falanga, Paolo Capuano, Silvia Scarpetta
Advancements in Road Lane Mapping: Comparative Fine-Tuning Analysis of Deep Learning-based Semantic Segmentation Methods Using Aerial Imagery
Xuanchen (Willow)Liu, Shuxin Qiao, Kyle Gao, Hongjie He, Michael A. Chapman, Linlin Xu, Jonathan Li
Convolutional neural networks applied to modification of images
Carlos I. Aguirre-Velez, Jose Antonio Arciniega-Nevarez, Eric Dolores-Cuenca
Residual Kolmogorov-Arnold Network for Enhanced Deep Learning
Ray Congrui Yu, Sherry Wu, Jiang Gui
AI-Driven Early Mental Health Screening with Limited Data: Analyzing Selfies of Pregnant Women
Gustavo A. Basílio, Thiago B. Pereira, Alessandro L. Koerich, Ludmila Dias, Maria das Graças da S. Teixeira, Rafael T. Sousa, Wilian H. Hisatugu, Amanda S. Mota, Anilton S. Garcia, Marco Aurélio K. Galletta, Hermano Tavares, Thiago M. Paixão
Art Forgery Detection using Kolmogorov Arnold and Convolutional Neural Networks
Sandro Boccuzzo, Deborah Desirée Meyer, Ludovica Schaerf
Radio Map Prediction from Aerial Images and Application to Coverage Optimization
Fabian Jaensch, Giuseppe Caire, Begüm Demir