Research

Papers for “image classification”

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

Title	Authors	Year	Source
Drop to Adapt: Learning Discriminative Features for Unsupervised Domain Adaptation	Seungmin Lee, Dongwan Kim, Namil Kim	2019	arxiv 1910.05562
Achieving Generalizable Robustness of Deep Neural Networks by Stability Training	Jan Laermann, Wojciech Samek, Nils Strodthoff	2019	arxiv 1906.00735
High Performance I/O For Large Scale Deep Learning	Alex Aizman, Gavin Maltby, Thomas Breuel	2020	arxiv 2001.01858
Database Meets Deep Learning: Challenges and Opportunities	Wei Wang, Meihui Zhang, Gang Chen	2019	arxiv 1906.08986
Towards a Design Framework for TNN-Based Neuromorphic Sensory Processing Units	Prabhu Vellaisamy, John Paul Shen	2022	arxiv 2205.14248
On the Transferability of Adversarial Examples between Encrypted Models	Miki Tanaka, Isao Echizen, Hitoshi Kiya	2022	arxiv 2209.02997
mFI-PSO: A Flexible and Effective Method in Adversarial Image Generation for Deep Neural Networks	Hai Shu, Ronghua Shi, Qiran Jia	2020	arxiv 2006.03243
Distributed Training of Deep Neural Networks with Theoretical Analysis: Under SSP Setting	Abhimanu Kumar, Pengtao Xie, Junming Yin	2015	arxiv 1512.02728
HyperSpectral classification with adaptively weighted L1-norm regularization and spatial postprocessing	Victor Stefan Aldea	2014	arxiv 1412.2684
Category Query Learning for Human-Object Interaction Classification	Chi Xie, Fangao Zeng, Yue Hu	2023	arxiv 2303.14005
An Adaptive Method Stabilizing Activations for Enhanced Generalization	Hyunseok Seung, Jaewoo Lee, Hyunsuk Ko	2025	arxiv 2506.08353
Comparative Analysis of CNN Performance in Keras, PyTorch and JAX on PathMNIST	Anida Nezović, Jalal Romano, Nada Marić	2025	arxiv 2507.12248
ModelVerification.jl: a Comprehensive Toolbox for Formally Verifying Deep Neural Networks	Tianhao Wei, Hanjiang Hu, Luca Marzari	2024	arxiv 2407.01639
First Three Years of the International Verification of Neural Networks Competition (VNN-COMP)	Christopher Brix, Mark Niklas Müller, Stanley Bak	2023	arxiv 2301.05815
Optimizing Class Distributions for Bias-Aware Multi-Class Learning	Mirco Felske, Stefan Stiene	2025	arxiv 2509.11588
A new bandwidth selection criterion for using SVDD to analyze hyperspectral data	Yuwei Liao, Deovrat Kakde, Arin Chaudhuri	2018	arxiv 1803.03328
Deep learning based prediction of Alzheimer's disease from magnetic resonance images	Manu Subramoniam, Aparna T. R., Anurenjan P. R.	2021	arxiv 2101.04961
The Simpler The Better: An Entropy-Based Importance Metric To Reduce Neural Networks' Depth	Victor Quétu, Zhu Liao, Enzo Tartaglione	2024	arxiv 2404.18949
Single Image Test-Time Adaptation for Segmentation	Klara Janouskova, Tamir Shor, Chaim Baskin	2023	arxiv 2309.14052
EmoCAM: Toward Understanding What Drives CNN-based Emotion Recognition	Youssef Doulfoukar, Laurent Mertens, Joost Vennekens	2024	arxiv 2407.14314

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