Frequency-Domain Feature Learning

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6 papers in the last four weeks, level with the four weeks before. 0.0% of all new papers.

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ChannelKAN: Multi-Scale Dual-Domain Channel Prediction via Hybrid CNN-KAN Architecture
May 11, 2026Nanqing Jiang, Zhangyao Song, Tao Guo +2Frequency-Domain Feature Learning Wireless Communications
School of Cyber Science and Engineering, Southeast University, Nanjing, China
CFSPMNet: Cross-subject Fourier-guided Spatial-Patch Mamba Network for EEG Motor Imagery Decoding in Stroke Patients
May 11, 2026Xiangkai Wang, Yun Zhao, Dongyi He +5Cross-Subject EEG Decoding Brain-Computer Interfaces
School of Artificial Intelligence, Chongqing University of Technology, Chongqing 401135, China; Chongqing Key Laboratory of Embodied Intelligence Perception and Autonomous Learning for Humanoid Robots; Key Laboratory of Advanced Equipment Intelligence of the Chongqing Education Commission, Chongqing 401135, China · School of Smart Health, Chongqing Polytechnic University of Electronic Technology, Chongqing 401131, China · Department of Language Science and Technology, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China +1
Frequency Matching in Spiking Neural Networks for mmWave Sensing
May 11, 2026Di Yu, Zhenyu Liao, Changze Lv +7Energy-Efficient ML Frequency-Domain Feature Learning
College of Computer Science and Technology, Zhejiang University, Hangzhou, China · School of Computer Science, Fudan University, Shanghai, China · Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China +1
Frequency Adapter with SAM for Generalized Medical Image Segmentation
May 11, 2026Phuoc-Nguyen Bui, Van-Nguyen Pham, Duc-Tai Le +2Frequency-Domain Feature Learning Domain Generalization
Sungkyunkwan University, Korea
Spectral Transformer Neural Processes
May 10, 2026Xianhe Chen, Hao Chen, Yingzhen LiTransformer Neural Processes
University of Cambridge · Tencent · Imperial College London
Hierarchical Multi-Scale Graph Neural Networks: Scalable Heterophilous Learning with Oversmoothing and Oversquashing Mitigation
May 8, 2026Md Sazzad Hossen, Avimanyu SahooGraph Neural Networks Over-Squashing
University of Alabama in Huntsville, Huntsville, AL, USA.
Preliminary Insights in Chronos Frequency Data Understanding and Reconstruction
May 7, 2026Alessandro Pagani, Marco Cominelli, Liying Han +11Frequency-Domain Feature Learning Time Series Representation Learning
DII, University of Brescia, Italy. · DEIB, Politecnico di Milano, Italy. · ECE Department, University of California, Los Angeles, USA. +6
Harmonized Feature Conditioning and Frequency-Prompt Personalization for Multi-Rater Medical Segmentation
May 6, 2026Sanaz Karimijafarbigloo, Armin Khosravi, Alireza Kheyrkhah +3Medical Image Analysis Frequency-Domain Feature Learning
Faculty of Informatics and Data Science, University of Regensburg, Regensburg, Germany · Sharif University of Technology, Tehran, Iran · Iran University of Science and Technology, Tehran, Iran +3
SpecPL: Disentangling Spectral Granularity for Prompt Learning
May 6, 2026Jingtao Zhou, Xirui Kang, Feiyang Huang +1VLM Adaptation Frequency-Domain Feature Learning
Department of Electrical Engineering, City University of Hong Kong, Hong Kong SAR.
Triple Spectral Fusion for Sensor-based Human Activity Recognition
May 4, 2026Ye Zhang, Longguang Wang, Qing Gao +3Graph Signal Processing Human Activity Recognition
School of Electronics and Communication Engineering, the Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, Shenzhen 518107, China · Aviation University of Air Force, Changchun 130012, China · College of Computer Science, Chongqing University, Chongqing 400044, China +1
RAFNet: Region-Aware Fusion Network for Pansharpening
May 4, 2026Jianing Zhang, Zijian Zhou, Kai SunDynamic Convolution Frequency-Domain Feature Learning
College of Artificial Intelligence, Xi’an Jiaotong University, Xi’an 710049, China · School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an 710049, China
Decompose to Understand, Fuse to Detect: Frequency-Decoupled Anomaly Detection for Encrypted Network Traffic
May 3, 2026Xinglin Lian, Chengtai Cao, Ting Zhong +3Frequency-Domain Feature Learning Network Intrusion Detection
School of Information and Software Engineering, University of Electronic Science and Technology of China · Department of Computer Science, City University of Hong Kong · Department of Computer Science and Engineering, Hong Kong University of Science and Technology +1
FEDIN: Frequency-Enhanced Deep Interest Network for Click-Through Rate Prediction
May 3, 2026Zenan Dai, Jinpeng Wang, Junwei Pan +3Sequential Recommendation Frequency-Domain Feature Learning
Tsinghua University Shenzhen, China · Harbin Institute of Technology, Shenzhen Shenzhen, China · Tencent Shenzhen, China
CGFformer: Cluster-Guidance Frequency Transformer for Pansharpening
May 2, 2026Zijian Zhou, Jianing Zhang, Kai Sun +3Frequency-Domain Feature Learning Remote Sensing
College of Artificial Intelligence, Xi’an Jiaotong University, Xi’an, 710049, China · School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, 710049, China · School of Computer Science and Technology, Xi’an Jiaotong University, Xi’an, 710049, China
PhaseNet++: Phase-Aware Frequency-Domain Anomaly Detection for Industrial Control Systems via Phase Coherence Graphs
Apr 30, 2026Raviteja Bommireddy, Varshith Bandaru, Lohith Pakala +1Cyber-Physical Systems Frequency-Domain Feature Learning
Department of CSE IIITDM Kancheepuram Chennai, India
Beyond the Baseband: Adaptive Multi-Band Encoding for Full-Spectrum Bioacoustics Classification
Apr 30, 2026Eklavya Sarkar, Marius Miron, David Robinson +6Audio Representation Learning Frequency-Domain Feature Learning
Earth Species Project
AdaMamba: Adaptive Frequency-Gated Mamba for Long-Term Time Series Forecasting
Apr 25, 2026Xudong Jiang, Mingshan Loo, Hanchen Yang +5Multivariate Time Series Forecasting Long-Term Time Series Forecasting
Tongji University Shanghai, China · Fudan University Shanghai, China
NAKUL-Med: Spectral-Graph State Space Models with Dynamics Kernels for Medical Signals
Apr 24, 2026Badri N. Patro, Vijay S. AgneeswaranElectroencephalography Neural Decoding
Microsoft
Unlocking Optical Prior: Spectrum-Guided Knowledge Transfer for SAR Generalized Category Discovery
Apr 24, 2026Jingyuan Xia, Ruikang Hu, Ye Li +3Domain Adaptation Frequency-Domain Feature Learning
College of Electronic Science and Technology, National University of Defense Technology, Changsha, 410073, China · State Key Laboratory of Complex System Simulation and Modeling Technology, Beijing, 100091, China
Convergent Evolution: How Different Language Models Learn Similar Number Representations
Apr 22, 2026Deqing Fu, Tianyi Zhou, Mikhail Belkin +2Fourier Feature Embeddings Frequency-Domain Feature Learning
University of Southern California · UC San Diego
Latent Fourier Transform
Apr 20, 2026Mason Wang, Cheng-Zhi Anna HuangControllable Music Generation Frequency-Domain Feature Learning
CSAIL
Exploring Boundary-Aware Spatial-Frequency Fusion for Camouflaged Object Detection
Apr 20, 2026Song Yu, Yang Hu, Haokang Ding +2Frequency-Domain Feature Learning Object Detection
School of Computer Science and Engineering, Central South University, Changsha, China
Unveiling Deepfakes: A Frequency-Aware Triple Branch Network for Deepfake Detection
Apr 19, 2026Qihao Shen, Jiaxing Xuan, Zhenguang Liu +5Frequency-Domain Feature Learning Deepfake Detection
State Key Laboratory of Blockchain and Data Security, Zhejiang University, Hangzhou, China · State Grid Blockchain Technology (Beijing) Co., Ltd., Beijing, China · Hangzhou High-Tech Zone (Binjiang) Institute of Blockchain and Data Security +3
Adaptive receptive field-based spatial-frequency feature reconstruction network for few-shot fine-grained image classification
Apr 18, 2026Linyue Zhang, Wenyi Zeng, Zicheng Pan +6Frequency-Domain Feature Learning Fine-Grained Image Classification
School of Electronic Information and Artificial Intelligence, Shaanxi University of Science and Technology, Xi’an, Shaanxi Province, China · School of Electrical Engineering and Computer Science, the University of Queensland, QLD, Australia · Institute for Integrated and Intelligent Systems, Griffith University, QLD, Australia +4
Hybrid Spectro-Temporal Fusion Framework for Structural Health Monitoring
Apr 17, 2026Jongyeop Kim, Jinki Kim, Doyun LeeFrequency-Domain Feature Learning Multiscale Time-Series Modeling
aDepartment of Information Technology, Georgia Southern University Statesboro, GA, USA · bDepartment of Mechanical Engineering, Georgia Southern University Statesboro, GA, USA · cDepartment of Civil Engineering and Construction, Georgia Southern University Statesboro, GA, USA
Graph self-supervised learning based on frequency corruption
Apr 17, 2026Haojie Li, Mengjiao Zhang, Guanfeng Liu +3Graph Neural Networks Graph Representation Learning
School of Data Science, Qingdao University of Science and Technology Qingdao, China · School of Information Science and Technology, Qingdao University of Science and Technology Qingdao, China · School of Computing, Macquarie University Sydney, Australia
Frequency-Enhanced Dual-Subspace Networks for Few-Shot Fine-Grained Image Classification
Apr 16, 2026Meijia Wang, Guochao Wang, Haozhen Chu +4Frequency-Domain Feature Learning Fine-Grained Image Classification
School of Electronic Information and Artificial Intelligence, Shaanxi University of Science and Technology, Xi’an 710000, China
FSDETR: Frequency-Spatial Feature Enhancement for Small Object Detection
Apr 16, 2026Jianchao Huang, Fengming Zhang, Haibo Zhu +1Frequency-Domain Feature Learning Small Object Detection
School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China
HAMSA: Scanning-Free Vision State Space Models via SpectralPulseNet
Apr 16, 2026Badri N. Patro, Vijay S. AgneeswaranFrequency-Domain Feature Learning Visual SSMs
Microsoft
FreqTrack: Frequency Learning based Vision Transformer for RGB-Event Object Tracking
Apr 16, 2026Jinlin You, Muyu Li, Xudong ZhaoVision Transformer Frequency-Domain Feature Learning
Dalian University of Technology

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ChannelKAN: Multi-Scale Dual-Domain Channel Prediction via Hybrid CNN-KAN Architecture

Nanqing Jiang, Zhangyao Song, Tao Guo, Xiaoyu Zhao+1

School of Cyber Science and Engineering, Southeast University, Nanjing, China

Frequency-Domain Feature Learning Wireless Communications

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Accurate channel state information (CSI) prediction is essential for improving the reliability and spectral efficiency of massive MIMO-OFDM systems in high-mobility scenarios. Existing deep learning methods struggle to jointly capture short-term local variations and long-range nonlinear dependencies in CSI sequences. To address this challenge, we propose ChannelKAN, a hybrid CNN-KAN channel prediction model with multi-scale frequency domain information enhancement. The key insight is that CNNs and Kolmogorov-Arnold Networks (KANs) are naturally complementary: CNNs extract intra-time-step local spatial-frequency correlations, while KANs with learnable Chebyshev polynomial activations fit inter-time-step nonlinear temporal evolution in a holistic manner. Specifically, a dual-domain expansion module first generates complementary frequency-domain and delay-domain CSI representations. A multi-scale frequency information enhancement module then retains dominant spectral components at multiple scales to strengthen key features and suppress noise. Next, a CNN-KAN feature extraction module captures local correlations via cascaded convolutions and models long-range dependencies via Chebyshev KAN layers. Finally, a dual-domain fusion module adaptively integrates features from both branches to produce the prediction. Experiments on 3GPP-compliant QuaDRiGa datasets demonstrate that ChannelKAN outperforms RNN, LSTM, GRU, CNN, and Transformer baselines in normalized mean square error (NMSE), spectral efficiency (SE), and bit error rate (BER) across various velocities and signal-to-noise ratios. Ablation studies further confirm the effectiveness of each proposed module.

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