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
Adapting Vision Foundation Models for Robust Cloud Segmentation in Remote Sensing Images
Xuechao Zou, Shun Zhang, Kai Li, Shiying Wang, Junliang Xing, Lei Jin, Congyan Lang, Pin Tao
Incremental Label Distribution Learning with Scalable Graph Convolutional Networks
Ziqi Jia, Xiaoyang Qu, Chenghao Liu, Jianzong Wang
Attention-guided Spectrogram Sequence Modeling with CNNs for Music Genre Classification
Aditya Sridhar
Autoassociative Learning of Structural Representations for Modeling and Classification in Medical Imaging
Zuzanna Buchnajzer, Kacper Dobek, Stanisław Hapke, Daniel Jankowski, Krzysztof Krawiec
LightFFDNets: Lightweight Convolutional Neural Networks for Rapid Facial Forgery Detection
Günel Jabbarlı, Murat Kurt
Edge-Enhanced Dilated Residual Attention Network for Multimodal Medical Image Fusion
Meng Zhou, Yuxuan Zhang, Xiaolan Xu, Jiayi Wang, Farzad Khalvati
FIAS: Feature Imbalance-Aware Medical Image Segmentation with Dynamic Fusion and Mixing Attention
Xiwei Liu, Min Xu, Qirong Ho
A Novel Adaptive Hybrid Focal-Entropy Loss for Enhancing Diabetic Retinopathy Detection Using Convolutional Neural Networks
Pandiyaraju V, Santhosh Malarvannan, Shravan Venkatraman, Abeshek A, Priyadarshini B, Kannan A
BiDense: Binarization for Dense Prediction
Rui Yin, Haotong Qin, Yulun Zhang, Wenbo Li, Yong Guo, Jianjun Zhu, Cheng Wang, Biao Jia
CNN-Based Classification of Persian Miniature Paintings from Five Renowned Schools
Mojtaba Shahi, Roozbeh Rajabi, Farnaz Masoumzadeh
STLight: a Fully Convolutional Approach for Efficient Predictive Learning by Spatio-Temporal joint Processing
Andrea Alfarano, Alberto Alfarano, Linda Friso, Andrea Bacciu, Irene Amerini, Fabrizio Silvestri
On the Universal Statistical Consistency of Expansive Hyperbolic Deep Convolutional Neural Networks
Sagar Ghosh, Kushal Bose, Swagatam Das
Flow reconstruction in time-varying geometries using graph neural networks
Bogdan A. Danciu, Vito A. Pagone, Benjamin Böhm, Marius Schmidt, Christos E. Frouzakis
DEEGITS: Deep Learning based Framework for Measuring Heterogenous Traffic State in Challenging Traffic Scenarios
Muttahirul Islam, Nazmul Haque, Md. Hadiuzzaman