Copertina

KAN-Mixers: a new deep learning architecture for image classification

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Canuto, Jorge Luiz dos Santos, Aylon, Linnyer Beatrys Ruiz, de Souza, Rodrigo Clemente Thom
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Computer Vision and Pattern Recognition Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

A review of deep learning-based information fusion techniques for multimodal medical image classification
di: Li, Yihao, et al.
Pubblicazione: (2024)

SYSTEMATIC LITERATURE REVIEW ON HUMANITARIAN OPERATIONS: RESOURCE OPTIMIZATION AND LOGISTICS IN FORCED DISPLACEMENT SCENARIOS
di: Santiago Sidon da Rocha, Leonardo, et al.
Pubblicazione: (2025)

A deep learning pipeline for PAM50 subtype classification using histopathology images and multi-objective patch selection
di: Borji, Arezoo, et al.
Pubblicazione: (2026)

A multimodal deep learning architecture for smoking detection with a small data approach
di: Lakatos, Robert, et al.
Pubblicazione: (2023)

Deep transfer learning for image classification: a survey
di: Plested, Jo, et al.
Pubblicazione: (2022)

Demystifying KAN for Vision Tasks: The RepKAN Approach
di: Cheon, Minjong
Pubblicazione: (2026)

Hybrid Classical-Quantum architecture for vectorised image classification of hand-written sketches
di: Cordero, Y., et al.
Pubblicazione: (2024)

MixerCSeg: An Efficient Mixer Architecture for Crack Segmentation via Decoupled Mamba Attention
di: Zhao, Zilong, et al.
Pubblicazione: (2026)

Impact of domain adaptation in deep learning for medical image classifications
di: Wu, Yihang, et al.
Pubblicazione: (2026)

KAN See In the Dark
di: Ning, Aoxiang, et al.
Pubblicazione: (2024)

FedDropoutAvg: Generalizable federated learning for histopathology image classification
di: Gunesli, Gozde N., et al.
Pubblicazione: (2021)

Individual mapping of large polymorphic shrubs in high mountains using satellite images and deep learning
di: Khaldi, Rohaifa, et al.
Pubblicazione: (2024)

Vision Eagle Attention: a new lens for advancing image classification
di: Hasan, Mahmudul
Pubblicazione: (2024)

FFNet: MetaMixer-based Efficient Convolutional Mixer Design
di: Yun, Seokju, et al.
Pubblicazione: (2024)

Self-learned representation-guided latent diffusion model for breast cancer classification in deep ultraviolet whole surface images
di: Afshin, Pouya, et al.
Pubblicazione: (2026)

Self-supervised learning of imaging and clinical signatures using a multimodal joint-embedding predictive architecture
di: Li, Thomas Z., et al.
Pubblicazione: (2025)

Using deep learning for predicting cleansing quality of colon capsule endoscopy images
di: Sharma, Puneet, et al.
Pubblicazione: (2026)

SIAM: A Simple Alternating Mixer for Video Prediction
di: Zheng, Xin, et al.
Pubblicazione: (2023)

Improving action classification with brain-inspired deep networks
di: Aglinskas, Aidas, et al.
Pubblicazione: (2025)

STCL:Curriculum learning Strategies for deep learning image steganography models
di: Liu, Fengchun, et al.
Pubblicazione: (2025)

A comprehensive overview of deep learning models for object detection from videos/images
di: Zulfqar, Sukana, et al.
Pubblicazione: (2026)

Training deep learning based dynamic MR image reconstruction using synthetic fractals
di: Raman, Anirudh, et al.
Pubblicazione: (2026)

KM-UNet KAN Mamba UNet for medical image segmentation
di: Zhang, Yibo
Pubblicazione: (2025)

Brain-like emergent properties in deep networks: impact of network architecture, datasets and training
di: Rajesh, Niranjan, et al.
Pubblicazione: (2024)

Precise localization of corneal reflections in eye images using deep learning trained on synthetic data
di: Byrne, Sean Anthony, et al.
Pubblicazione: (2023)

Pediatric brain tumor classification using digital histopathology and deep learning: evaluation of SOTA methods on a multi-center Swedish cohort
di: Tampu, Iulian Emil, et al.
Pubblicazione: (2024)

An analysis of data variation and bias in image-based dermatological datasets for machine learning classification
di: Filho, Francisco, et al.
Pubblicazione: (2025)

Can we trust deep learning models diagnosis? The impact of domain shift in chest radiograph classification
di: Pooch, Eduardo H. P., et al.
Pubblicazione: (2019)

K-U-KAN: Koopman-Enhanced U-KAN for 3D Dental Reconstruction from a Single Panoramic X-ray Radiograph
di: Parida, Bikram Keshari, et al.
Pubblicazione: (2026)

PoM: A Linear-Time Replacement for Attention with the Polynomial Mixer
di: Picard, David, et al.
Pubblicazione: (2026)

Modality-Aware and Shift Mixer for Multi-modal Brain Tumor Segmentation
di: Huang, Zhongzhen, et al.
Pubblicazione: (2024)

Deep learning for automated detection of breast cancer in deep ultraviolet fluorescence images with diffusion probabilistic model
di: Ghahfarokhi, Sepehr Salem, et al.
Pubblicazione: (2024)

A prior information informed learning architecture for flying trajectory prediction
di: Huang, Xianda, et al.
Pubblicazione: (2026)

Identifying bias in CNN image classification using image scrambling and transforms
di: Erukude, Sai Teja
Pubblicazione: (2025)

Explainable concept mappings of MRI: Revealing the mechanisms underlying deep learning-based brain disease classification
di: Tinauer, Christian, et al.
Pubblicazione: (2024)

Xeno-learning: knowledge transfer across species in deep learning-based spectral image analysis
di: Sellner, Jan, et al.
Pubblicazione: (2024)

A detection-task-specific deep-learning method to improve the quality of sparse-view myocardial perfusion SPECT images
di: Yang, Zezhang, et al.
Pubblicazione: (2025)

Detection of subclinical atherosclerosis by image-based deep learning on chest x-ray
di: Gallone, Guglielmo, et al.
Pubblicazione: (2024)

Smartphone region-wise image indoor localization using deep learning for indoor tourist attraction
di: Higa, Gabriel Toshio Hirokawa, et al.
Pubblicazione: (2024)

DermAI: Clinical dermatology acquisition through quality-driven image collection for AI classification in mobile
di: Bezerra, Thales, et al.
Pubblicazione: (2025)