Research

Papers for “imagenet”

Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.

Title	Authors	Year	Source
FFT-based Selection and Optimization of Statistics for Robust Recognition of Severely Corrupted Images	Elena Camuffo, Umberto Michieli, Jijoong Moon	2024	arxiv 2403.14335
Comparison of Different Deep Neural Network Models in the Cultural Heritage Domain	Teodor Boyadzhiev, Gabriele Lagani, Luca Ciampi	2025	arxiv 2504.21387
Dynamic Spectral Backpropagation for Efficient Neural Network Training	Mannmohan Muthuraman	2025	arxiv 2505.23369
Tensor Reordering for CNN Compression	Matej Ulicny, Vladimir A. Krylov, Rozenn Dahyot	2020	arxiv 2010.12110
Contextual fusion enhances robustness to image blurring	Shruti Joshi, Aiswarya Akumalla, Seth Haney	2024	arxiv 2406.05120
End-to-End Optimization of JPEG-Based Deep Learning Process for Image Classification	Siyu Qi, Lahiru D. Chamain, Zhi Ding	2023	arxiv 2308.05840
Unsupervised Anomaly Detection with an Enhanced Teacher for Student-Teacher Feature Pyramid Matching	Mohammad Zolfaghari, Hedieh Sajedi	2025	arxiv 2512.18219
TropNNC: Structured Neural Network Compression Using Tropical Geometry	Konstantinos Fotopoulos, Petros Maragos, Panagiotis Misiakos	2024	arxiv 2409.03945
Hybrid ANN-SNN Pipeline with Local Plasticity	Denis Larionov, Khairutin Shtanchaev, Mikhail Kiselev	2026	arxiv 2606.20151
Shapley Neuron Values for Continual Learning: Which Neurons Matter Most?	Mohammad Ali Vahedifar, Abhisek Ray, Qi Zhang	2026	arxiv 2605.15877
TRAM: Training Approximate Multiplier Structures for Low-Power AI Accelerators	Chang Meng, Hanyu Wang, Yuyang Ye	2026	arxiv 2605.08231
Self-Supervised Class Incremental Learning	Zixuan Ni, Siliang Tang, Yueting Zhuang	2021	arxiv 2111.11208
Mugs: A Multi-Granular Self-Supervised Learning Framework	Pan Zhou, Yichen Zhou, Chenyang Si	2022	arxiv 2203.14415
Reduce, Reuse, Recycle: Improving Training Efficiency with Distillation	Cody Blakeney, Jessica Zosa Forde, Jonathan Frankle	2022	arxiv 2211.00683
On Distillation of Guided Diffusion Models	Chenlin Meng, Robin Rombach, Ruiqi Gao	2022	arxiv 2210.03142
SpectFormer: Frequency and Attention is what you need in a Vision Transformer	Badri N. Patro, Vinay P. Namboodiri, Vijay Srinivas Agneeswaran	2023	arxiv 2304.06446
Scaling Neural Network Performance through Customized Hardware Architectures on Reconfigurable Logic	Michaela Blott, Thomas B. Preusser, Nicholas Fraser	2018	arxiv 1807.03123
Bi-Real Net: Enhancing the Performance of 1-bit CNNs With Improved Representational Capability and Advanced Training Algorithm	Zechun Liu, Baoyuan Wu, Wenhan Luo	2018	arxiv 1808.00278
MixTrain: Scalable Training of Verifiably Robust Neural Networks	Shiqi Wang, Yizheng Chen, Ahmed Abdou	2018	arxiv 1811.02625
Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations	Yiping Lu, Aoxiao Zhong, Quanzheng Li	2017	arxiv 1710.10121

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