Dynamic Neural Networks: A Survey

Deep Residual Learning for Image Recognition

He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474

Attention Is All You Need

Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., & Polosukhin, I. (2017) · arXiv · doi:10.48550/arxiv.1706.03762 · Cited by 120,404

Very Deep Convolutional Networks for Large-Scale Image Recognition

Simonyan, K., & Zisserman, A. (2014) · arXiv · doi:10.48550/arxiv.1409.1556 · Cited by 114,148

Long Short-Term Memory

Hochreiter, S., & Schmidhuber, J. (1997) · Neural Computation · doi:10.1162/neco.1997.9.8.1735 · Cited by 102,318

Adam: A Method for Stochastic Optimization

Kingma, D. P., & Ba, J. (2014) · arXiv · doi:10.48550/arxiv.1412.6980 · Cited by 98,946

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2019) · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) · doi:10.18653/v1/n19-1423 · Cited by 54,325

Densely Connected Convolutional Networks

Huang, G., Liu, Z., Van Der Maaten, L., & Weinberger, K. Q. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.243 · Cited by 48,566

Squeeze-and-Excitation Networks

Hu, J., Shen, L., & Sun, G. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00745 · Cited by 35,667

CBAM: Convolutional Block Attention Module

Woo, S., Park, J., Lee, J.-Y., & Kweon, I. S. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01234-2_1 · Cited by 25,853

Language Models are Few-Shot Learners

Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al. (2020) · arXiv · doi:10.48550/arxiv.2005.14165 · Cited by 23,372

Research on Neural Network-Assisted Input Optimization in Control System Frameworks

Xu, Y., & Wang, X. (2024) · Asia-Pacific Conference on Communications Technology and Computer Science (ACCTCS) · doi:10.1109/acctcs61748.2024.00080

Input Compression with Positional Consistency for Efficient Training and Inference of Transformer Neural Networks

Nagarajan, A., & Raghunathan, A. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-70362-1_5

Dynamic Gesture Recognition Using a Spatio-Temporal Adaptive Multiscale Convolutional Transformer Network

Chen, J., Tie, Y., Qi, L., & Liang, C. (2024) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn60899.2024.10650267

More Experts Than Galaxies: Conditionally-overlapping Experts With Biologically-Inspired Fixed RoutingPreprint

Shaier, S., Pereira, F., von der Wense, K., Hunter, L., & Jones, M. (2024) · arXiv (Cornell University) · doi:10.48550/arxiv.2410.08003

EncodingNet: A Novel Encoding-Based MAC Design for Efficient Neural Network Acceleration

Liu, B., Li, B., Zhang, G. L., Yin, X., Zhuo, C., & Schlichtmann, U. (2024) · IEEE transactions on circuits and systems for artificial intelligence. · doi:10.1109/tcasai.2024.3493035

Модель та метод навчання детектора об’єктів на аерозображенні з оптимізацією робастності та кількості обчислень

Москаленко, А. С., Zaretskyi, M., Vynohradov, M., & Babych, V. (2024) · Aerospace technic and technology · doi:10.32620/aktt.2024.5.11

Dynamic Inference and Top-down Attention in a Hierarchical Classification Network

Kelm, A. P., Hannemann, N., Heberle, B., Schmidt, L., Rolff, T., Wilms, C., Yaghoubi, E., & Frintrop, S. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-78186-5_15

Sampling Rate Adaptive Speaker Verification from Raw Waveforms

Abrol, V., Thakur, A., Gupta, A., Liu, X., & Shah, S. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-78104-9_25

Blind Restoration for Nonhomogeneous Hazy Images based on CycleGAN and Parameters-Adaptive Mechanism

Zhang, B., Zhang, Z., Ren, M., & Wang, Y. (2024) · International Conference on Advances in Image Processing (ICAIP) · doi:10.1145/3702370.3702385

ASRMF: Adaptive image super-resolution based on dynamic-parameter DNN with multi-feature prior

Zhang, Z., Wang, K., Cheng, L., & Xu, X. (2025) · Signal Processing · doi:10.1016/j.sigpro.2024.109880

Application of Big Data Technology in Mathematical Modeling Based on Neural Network Algorithm

Jing, L. (2025) · Lecture notes on data engineering and communications technologies · doi:10.1007/978-981-96-0208-7_73

LazyAct: Lazy actor with dynamic state skip based on constrained MDP

Zhang, H., Chen, Z., Deng, H., & Feng, C. (2025) · PLoS ONE · doi:10.1371/journal.pone.0318778

A Training Algorithm for Locally Recurrent Neural Networks Based on the Explicit Gradient of the Loss Function

Montisci, A., & Carcangiu, S. (2025) · Algorithms · doi:10.3390/a18020104

Input-Aware Slowdown Backdoor Attack on Dynamic Neural Networks

Guan, Z.-Q., Liu, J., He, Z., Miao, S., & Liu, D. (2025) · Journal of Circuits Systems and Computers · doi:10.1142/s0218126625502834

Utilizing Full-Dimensional Dynamic Convolution for Multi-Modal Gaze Tracking in Conversational Scenarios

Huang, F., & Qing, L. (2024) · International Annual Conference on Complex Systems and Intelligent Science (CSIS-IAC) · doi:10.1109/csis-iac63491.2024.10919405

Overcoming Catastrophic Interference: Neuroscience-inspired Models for Continuous Learning in Neural NetworksPreprint

Alashwal, H., Dabool, H., van Zyl, T., van der Haar, D., Chakravarthy, S., Deldari, S., Salim, F. D., Lerner, I., & Moustafa, A. (2025) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/up7yz_v1

TCDNet: Texture and Color Dynamic Network for Image Harmonization

Yue, S., Huang, H., Tang, Z., Zheng, Y., & Fang, Z. (2025) · Lecture notes in computer science · doi:10.1007/978-981-96-5812-1_20

Multi-granular dynamic interaction network for multimodal sarcasm detection

Lin, J., & Zhu, X. (2025) · Multimedia Systems · doi:10.1007/s00530-025-01786-6

Deep Learning Anytime Prediction via Enforcing Runtime Monotonicity for Early-Exit Activity Recognition

Liu, X., Zhang, L., Huang, W., Xiong, D., Fu, Z., Wu, H., & Song, A. (2025) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2025.3566808

Lightweight Energy Budget Prediction for Wireless Transceivers

Bieger, E. N. S., Bewiahn, T. A., & Fröhlich, A. A. (2025) · IEEE Wireless Communications and Networking Conference · doi:10.1109/wcnc61545.2025.10978504

Enhanced YOLOv8-Based Small Object Detection in Unmanned Aerial Vehicle (UAV) Perspective

Li, J., Yang, C., & Xu, Y. (2025) · Lecture notes in electrical engineering · doi:10.1007/978-981-96-4016-4_1

AuroraFlow, an Easy-to-Use, Low-Latency FPGA Communication Solution Demonstrated on Multi-FPGA Neural Network Inference

Pape, G., Wintermann, B., Jungemann, L., Lass, M., Meyer, M., Riebler, H., & Plessl, C. (2025) · International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies (HEART) · doi:10.1145/3728179.3728190

A Supernet-Only Framework for Federated Learning in Computationally Heterogeneous Scenarios

Chen, Y., Chen, D., & Zhong, C. (2025) · Applied Sciences · doi:10.3390/app15105666

De2r: Unifying DVFS and Early-Exit for Embedded AI Inference via Reinforcement Learning

He, Y., Li, J., Li, C., Yang, Q., Wang, Z., Du, H., Ren, J., & Yu, H. (2025) · Design, Automation, and Test in Europe · doi:10.23919/date64628.2025.10992707

ConNEF: An Encryption Framework for Deep Neural Network IP Protection

Wang, L., Hu, M., Xu, S., Zhao, M., & Chang, J. (2025) · International World Wide Web Conference (WWW) · doi:10.1145/3701716.3715470

Software-Hardware Exploration of Early-Exit Neural Networks on Edge Accelerators

Gong, Q., Duan, B., Miao, S., He, Z., & Liu, D. (2025) · IEEE Embedded Systems Letters · doi:10.1109/les.2025.3573404

Analysis of integrated real-time decision support systems based on neural networks and low-structured data

Demchyna, M. (2025) · Information Technology and Computer Engineering · doi:10.63341/vitce/1.2025.20

ESCAN: Efficient GPU sharing for cascade neural network inference

Wang, J., Shi, Y., Chen, Z., & Wen, M. (2025) · Neural Networks · doi:10.1016/j.neunet.2025.107703

Seasonal short-term load forecasting (STLF) using combined Social Spider Optimisation (SSO) and African Vulture Optimisation Algorithm (AVOA) in Artificial Neural Networks (ANN)

Ekedegwa, A. I. G., Ashigwuike, E. C., & Abdullahi, S. B. M. (2025) · Communication in Physical Sciences · doi:10.4314/cps.v12i3.32

A Simplified Smart Grid Simulation of Renewable Energy Integration and Battery Storage for Demand Response Optimization

Ohiri, P. C., Ogomaka Chrysogonus, C., Benson, M. E., & Anyalewechi Chika, J. (2025) · International Journal of Computer Applications · doi:10.5120/ijca2025925323

Resource-Efficient Sensor Fusion at the Edge via System-Wide Dynamic Gated Neural Networks

Singhal, C., Wu, Y., Malandrino, F., Contreras, S. G. L., Levorato, M., & Chiasserini, C. F. (2025) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2025.3586882

A Complex Scene Text Detection Method Based on Adaptive Scale Attention and Cross-scale Channel Fusion

-, D. X., Hu, Y., & Chuansheng, S. (2025) · International Symposium on Computer Technology and Information Science (ISCTIS) · doi:10.1109/isctis65944.2025.11065998

A Study of Dynamic Neural Network Framework Based on Data Preprocessing and PDE Integration

Liao, B., Wu, Z., Luo, L., Jiang, J., & Lu, G. (2025) · International Conference on Computer and Communication Systems (ICCCS) · doi:10.1109/icccs65393.2025.11069834

Data driven computer vision oriented image signal processing pipeline configuration

Zhou, W., Wang, H., Li, H., Zhu, M., Mao, Y., Ji, D., & Lou, X. (2026) · Neurocomputing · doi:10.1016/j.neucom.2026.134761

MNTSCC: A VMamba-Based Nonlinear Joint Source-Channel Coding for Semantic Communications

Li, C., Wang, C., Ding, C., Liao, Y., & Ye, Z. (2025) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2025.067440

AHT-ViT: Adaptive Halting Transformer with Planned Depth Execution

Shutov, V., & Asadulaev, A. (2025) · International Journal on Cybernetics & Informatics · doi:10.5121/ijci.2025.140404

Dynamic CNN-LSTM-Based Intrusion Detection System in Enterprise Financial Systems

Fu, L., & Shao, Z. (2025) · Journal of Circuits Systems and Computers · doi:10.1142/s0218126625504249

Joint Optimization of Deep Attention-Based Multimodal MRI Feature Fusion with Shape-Aware Loss Function and Monte Carol Dropout for Segmentation of Non-Ellipsoidal Brain TumorsPreprint

Gikera, R., Mambo, S. M., & Guarnera, A. (2025) · Research Square · doi:10.21203/rs.3.rs-7161017/v1

Enhancing Parameter Calibration in Land Surface Models Using a Multi-Task Surrogate Model within a Differentiable Parameter Learning FrameworkPreprint

Xie, W., Li, H., & Yoshimura, K. (2025) · doi:10.5194/egusphere-2026-4009

Lightweight self-attention and deep gated neural network (LSA-DGNet) for multiple neurological disease detection

Jain, S., Srivastava, R., & Pal, S. (2025) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2025.108621

Task Aware Dynamic Transformer for Arbitrary-Scale Image Super-ResolutionPreprint

wang, Z., Xu, T., Gong, C., Wang, H., & Xu, J. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5467513

Retraining-Free Mixed-Precision Quantization for Power Equipment Defect Detection via Layer-Aware Particle Swarm Optimization

Chen, K., Luo, L., & Li, X. (2025) · International Journal of Swarm Intelligence Research · doi:10.4018/ijsir.388948

From Regulation to Interconnection: Mapping the Evolution of the U.S. Interbank MarketPreprint

Owusu-Peprah, N. T., & Wang, H. (2025) · Research Square · doi:10.21203/rs.3.rs-7595106/v1

ERDE: Entropy-Regularized Distillation for Early-exitPreprint

Guidez, M., Duffner, S., Alpou, Y., Röth, O., & García, C. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5545796

Research on Image Classification Based on CNN-Transformer and ResNet Neural Network

Wang, Q. (2025) · International Conference on Electronic Communication and Artificial Intelligence (ICECAI) · doi:10.1109/icecai66283.2025.11171442

HERACLES: Hierarchical Semantic Communications for Distributed Dynamic Sensor Fusion

Qin, L., Wu, Y., Najeh, S., Levorato, M., & Chiasserini, C. F. (2025) · IEEE International Conference on Distributed Computing Systems (ICDCS) · doi:10.1109/icdcs63083.2025.00053

A Dynamic Feature Caching Mechanism for Accelerating CNN Real-time Inference

Hui, T., Li, Z., He, H., Yu, Z., & Bao, D. (2025) · International Joint Conference on Information and Communication Engineering (JCICE) · doi:10.1109/jcice66205.2025.11182067

LNBN: layer-flexible non-blocking bypass network-on-chip for accelerating DNN inference

Kang, S. B., Kim, W. H., & Han, T. H. (2025) · The Journal of Supercomputing · doi:10.1007/s11227-025-07913-4

LEAP: Lightweight Neural Network Inference Through Proactive Early-Exiting Prediction

Shen, Y., Li, X., Ma, Y., Cao, W., Zhao, J., & Zou, A. (2025) · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · doi:10.1109/tcad.2025.3621532

Neuroplasticity-Inspired Dynamic Artificial Neural Networks for Multi-Task Demand Forecasting

Żarski, M., & Nowaczyk, S. (2026) · IEEE Access · doi:10.1109/access.2026.3709101

CFPER: Coarse-to-Fine Part-Experts Retrieval for Efficient Person Re-identification

Wang, S., & Lu, M. (2025) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme59968.2025.11209843

Soft computing: An introduction to intelligent problem-solving techniques

Afaq, S. A., Faisal, M., Siddique, M., & Uzma, S. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-33881-6.00016-2

A novel hybrid load balancing technique for optimizing data center network performance

Niyasudeen, P. M., Kumar, A., Mani, M., Kuppuswamy, P., Gupta, S. K., & Al-Maliki, S. Q. A.-K. (2025) · AIP conference proceedings · doi:10.1063/5.0292511

CCE: A Content Creation Engine With Outlier and Mixed-Representation Computing, Semantic-Defined Instruction Generation for Video Diffusion

Tang, C., Huang, Z., Wang, W., Feng, X., He, Y., Fan, S., Wang, K., Sun, W., & Liu, Y. (2025) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2025.3622515

Parameters-adaptive mechanism based on degradation degree for nonhomogeneous image dehazing

Zhang, Z., Zhang, B., Cheng, L., Xu, X., & Ren, M. (2025) · Optics and Lasers in Engineering · doi:10.1016/j.optlaseng.2025.109454

Synchronization in Hybrid Feedforward-Recurrent Neural Networks with Stochastic Temporal Modulation

Sengupta, R. (2025) · International Conference on Intelligent Communication Networks and Computational Techniques (ICICNCT) · doi:10.1109/icicnct66124.2025.11232771

Accelerating Local AI on Consumer GPUs: A Hardware-Aware Dynamic Strategy for YOLOv10sPreprint

Masum, M. I., & Islam, M. (2025) · arXiv (Cornell University) · doi:10.48550/arxiv.2509.07928

Lifelong Morphology Learning for Deformable Embodied Agents

Wang, Y., Zhao, J., Yang, Y., Zhang, S., & Liu, H. (2025) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros60139.2025.11247624

Neural Implicit Representations for Object-Centric Machine Vision Tasks

Kim, Y., & Kang, J. (2025) · Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) · doi:10.1109/apsipaasc65261.2025.11249403

Investigation of optimized temporal convolutional network based on GKSO algorithm for lithium battery state of charge estimation

Zhou, J., Liu, K., Pei, Z., Chen, X., Feng, X., Huang, C., Jiang, Z., & Liao, P. (2025) · Energy · doi:10.1016/j.energy.2025.139491

Elastoformer: Enabling Dynamic Adaptivity via Elastic Model Transformation

Kalra, S., & Sapra, D. (2025) · ACM/IEEE Symposium on Edge Computing (SEC) · doi:10.1145/3769102.3770612

Toward QoE-Fairness for Video Streaming Over Heterogeneous Networks: An Innovative Bandwidth Allocation Mechanism

Su, Q., Huang, J., Li, W., Li, Z., Zhang, T., Jiang, W., & Wang, J. (2025) · IEEE Transactions on Networking · doi:10.1109/ton.2025.3638882

DyCoNovo: a De Novo Peptide Prediction Model Based on Dynamic Convolution and Phased Contrastive Learning

Liu, N., Qiu, N., Zhang, H., Liu, C., & Zhu, B. (2025) · International Congress on Image and Signal Processing (CISP) · doi:10.1109/cisp-bmei68103.2025.11259143

Early Exiting Predictive Coding Neural Networks for Edge AI

Zniber, A., Ghogho, M., Karrakchou, O., & Zakroum, M. (2025) · European Signal Processing Conference (EUSIPCO) · doi:10.23919/eusipco63237.2025.11226813 · Cited by 1

PERTINENCE: Input-Based Opportunistic Neural Network Dynamic Execution

Shende, O. B., Ananthanarayanan, G., & Traiola, M. (2026) · IEEE Access · doi:10.1109/access.2026.3707342

Intelligent design of squeeze casting gating system based on enhanced conditional generative adversarial networks and hypernetworks

Chen, Y., Wang, Z., Gao, J., Hu, K., Guo, L., Teng, Q., & Han, M. (2026) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-026-18256-6

Optimizing TinyML: User-oriented Trade-offs in Accuracy and Energy Consumption

Puślecki, T., & Walkowiak, K. M. (2025) · IEEE International Conference on Consumer Electronics - Berlin (ICCE-Berlin) · doi:10.1109/icce-berlin67488.2025.11277682

Cross-Domain Image Classification Based on Lightweight Backbone and AFR Module: Application in PACS Dataset and Edge Devices

Xv, H. (2025) · International Conference on Electronic Information Engineering and Computer Science (EIECS) · doi:10.1109/eiecs67708.2025.11283537

ERA : Expert Retrieval and Assembly for Early Action Prediction

Rahmani, H. (2022) · Lancaster EPrints (Lancaster University)

D-DGC : une approche dynamique pour le clustering profond des graphes attribués

Touati, M. F. (2022) · Archipel (Université du Québec à Montréal)

Predicting stock market trends using time-series classification with dynamic neural networks

Mocanu, R. (2023) · Papyrus : Institutional Repository (Université de Montréal) · doi:10.71781/10507

Speech Separation in Noisy Reverberant Acoustic Environments

Ravenscroft, W. (2024) · White Rose eTheses Online (University of Leeds, The University of Sheffield, University of York)

Toward Temporal Efficient Spiking Neural Network via Dynamic Training and Inference

Xia, N., Liu, X., Wei, S., Chen, L., & Ping, H. (2025) · IEEE Transactions on Emerging Topics in Computational Intelligence · doi:10.1109/tetci.2025.3628761

Faster Classification of Time-Series Input Streams

Agrawal, K., Baruah, S., Guo, Z., Li, J., Reghenzani, F., Yang, K., & Zhao, J. (2025) · DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) · doi:10.4230/lipics.ecrts.2025.13

Multilayer dynamical neural observer tune with the attractive ellipsoid method for uncertain nonlinear systems

Reza, V., Torres, J., & Guerrero, J. (2025) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2025.12.124

DCMCF: Dynamic Cross‐Modal Context Fusion for Image‐Based Person Search

Nian, F., Wang, Y., Liu, A., Fu, Y., & Gu, Y. (2025) · IET Image Processing · doi:10.1049/ipr2.70263

Toward Unified Expertise: Learning a Single Vision Model From Diverse Perception

Chen, Z., Ding, M., Shen, Y., Miller, E. G., & Gan, C. (2025) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2025.3647880

Dataset Pruning Using Early Exit Networks

Görmez, A., & Koyuncu, E. (2025) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3785502

Prediction of torsional characteristics of clutch driven disc assemblies based on machine learning methods

Li, L., Jiao, Y., Li, X., Zhang, Y., Liu, L., Chen, G., & Song, D. (2025) · Eksploatacja i Niezawodnosc - Maintenance and Reliability · doi:10.17531/ein/215705

Trustworthy Distributed Decision-Making for Multi-view Sensing Data

Song, Z., Pan, Y., Zhao, M., Ameen, M., Wang, Z., & Wang, P. (2026) · Communications in computer and information science · doi:10.1007/978-981-95-2581-2_18

PyraFuseNet: Adaptive Dual-Path Pyramid Fusion Network for Resource-Efficient Image Recognition

Devadiga, P., & Kundhavai, K. R. (2026) · Lecture notes in electrical engineering · doi:10.1007/978-981-95-0887-7_21

Sistema de controle para prótese ativa de joelho utilizando Deep Learning embarcado

Yamashita, J. V. Y. B. (2024) · LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)

Image Singularity Scattering Representation Learning Classification

Gao, J., Li, L., Liu, X., Jiao, L., Chen, P., Guo, Y., Liu, F., & Yang, S. (2026) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2026.3651091

Neuronal Controller Based on the Inverse Convolution of the Standard Output Signal Training

Nakonechnyi, M., Ivakhiv, O., Świsulski, D., Rudyk, Y., & Kopot, R. (2025) · IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) · doi:10.1109/idaacs68557.2025.11322354

Visual-language active search for wide-area remote sensing imagery

Xu, N., Yao, K., Yang, R., & Li, C. (2026) · Pattern Recognition · doi:10.1016/j.patcog.2026.113106

Multiscale Spatial-Frequency Learning for Degradation Decoupling in RS Image Restoration

Zhang, J., Li, L., Jiao, L., Liu, X., Liu, F., Ma, W., & Yang, S. (2026) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2026.3654414

[SoK] Systematizing Inference Placement For Deep Learning Across Edge And Cloud Platforms: A Multi-Objective Optimization Perspective

Zhang, Z., & Matta, I. (2025) · Journal of Systems Research · doi:10.5070/sr3.62212

Reinforcement Learning Based Model Adaptation and Partition for Dynamic DNN Empowered Mobile Vision

Liu, Y., Xiao, L., Li, T., Lv, Z., Qiao, Z., & Xiong, H. (2026) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2026.3665503

A Dynamic Application Configuration and Capacity-Aware Offloading System for MEC Optimization

Deng, X., Ju, B., Chen, H., Pei, S., Boukerche, A., Sun, P., & Song, L. (2026) · IEEE Internet of Things Journal · doi:10.1109/jiot.2026.3667205

TLDA: A lightweight and adaptive deep learning framework for accurate monthly runoff forecasting

Xu, D.-M., Zeng, Q.-Q., Wang, W., & Ma, Q. (2026) · Applied Soft Computing · doi:10.1016/j.asoc.2026.114939

MobileNetV3 for Mobile Gaming: A Confidence-Based Analysis of Model Performance on Structured ImageNet Subsets

Wang, Z. (2025) · International Conference on Computer Communication, Networks and Information Science (CCNIS) · doi:10.1109/ccnis69465.2025.00076

Signal Classification In Communication System Using Machine Learning

Anwar, M., Bazzal, A., Sohail, M., & Toor, W. T. (2025) · International Conference on Innovative Computing (ICIC) · doi:10.1109/icic68258.2025.11413141

Cross-Scale Multi-Task Lightweight Hyper-Network Model for Remote Sensing Target Classification

Xu, S., Hu, S., Liao, N., Yuan, Z., Sun, X., Zhuang, J., & Yan, Y. (2026) · Remote Sensing · doi:10.3390/rs18060844

Unleashing the Potential of Coverage Representation in Deep Learning-Based Fault Localization

Wang, J., Lei, Y., Xie, H., & Liu, C. (2026) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2026.3674478

Moral Decision Training Platform AI and Psychological Modeling for Information Management

Zhang, J., & Zhang, S. (2026) · Information Resources Management Journal · doi:10.4018/irmj.404755

Adaptive Modulation Inference via Input Skipping and Budget-Efficient Exiting

Xiang, K., Zhang, X., Zheng, X., Ma, Y., Meng, F., & Zhang, Q. (2025) · Globecom · doi:10.1109/globecom59602.2025.11432692

Securing Driver Safety: A Review on Adversarial Robustness for Computer Vision-Based Drowsiness Detection

Shymala Gowri, S., & S., S. S. (2026) · International Conference on Intelligent Systems for Communication, IoT and Security (ICISCoIS) · doi:10.1109/iciscois62701.2026.11447822

Research on team efficacy in CBA games based on complex network theory

Guo, W., Dong, R., Dong, T., & Chen, L. (2026) · PLoS ONE · doi:10.1371/journal.pone.0344684

Carbon-Neutral Foundation Models Through Adaptive Transform Compression

Maggu, J. (2026) · IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI) · doi:10.1109/iatmsi68868.2026.11465411

Data-driven control for grid-forming inverter-based generator in microgrid

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