Research

Papers for “image classification”

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

Title	Authors	Year	Source
Exploring Explainability Methods for Graph Neural Networks	Harsh Patel, Shivam Sahni	2022	arxiv 2211.01770
A Functional Data Framework For Analyzing Shapes and Textures in Images	Issam-Ali Moindjié	2026	arxiv 2606.10969
Fractional Stochastic Neural Networks	Yuecai Han, Jianming Xu	2026	arxiv 2606.29438
Carrying out CNN Channel Pruning in a White Box	Yuxin Zhang, Mingbao Lin, Chia-Wen Lin	2021	arxiv 2104.11883
A memory-efficient neural ODE framework based on high-level adjoint differentiation	Hong Zhang, Wenjun Zhao	2022	arxiv 2206.01298
Pooling is neither necessary nor sufficient for appropriate deformation stability in CNNs	Avraham Ruderman, Neil C. Rabinowitz, Ari S. Morcos	2018	arxiv 1804.04438
Learning from Web Data: the Benefit of Unsupervised Object Localization	Xiaoxiao Sun, Liang Zheng, Yu-Kun Lai	2018	arxiv 1812.09232
Deeply-supervised Knowledge Synergy	Dawei Sun, Anbang Yao, Aojun Zhou	2019	arxiv 1906.00675
Deep Context-Aware Kernel Networks	Mingyuan Jiu, Hichem Sahbi	2019	arxiv 1912.12735
Algorithm-hardware Co-design for Deformable Convolution	Qijing Huang, Dequan Wang, Yizhao Gao	2020	arxiv 2002.08357
Shoestring: Graph-Based Semi-Supervised Learning with Severely Limited Labeled Data	Wanyu Lin, Zhaolin Gao, Baochun Li	2019	arxiv 1910.12976
Utilizing Explainable AI for Quantization and Pruning of Deep Neural Networks	Muhammad Sabih, Frank Hannig, Juergen Teich	2020	arxiv 2008.09072
Attention Augmented Convolutional Networks	Irwan Bello, Barret Zoph, Ashish Vaswani	2019	arxiv 1904.09925
Assessing The Importance Of Colours For CNNs In Object Recognition	Aditya Singh, Alessandro Bay, Andrea Mirabile	2020	arxiv 2012.06917
Learning Data Augmentation Strategies for Object Detection	Barret Zoph, Ekin D. Cubuk, Golnaz Ghiasi	2019	arxiv 1906.11172
Single-bit-per-weight deep convolutional neural networks without batch-normalization layers for embedded systems	Mark D. McDonnell, Hesham Mostafa, Runchun Wang	2019	arxiv 1907.06916
A study on the Interpretability of Neural Retrieval Models using DeepSHAP	Zeon Trevor Fernando, Jaspreet Singh, Avishek Anand	2019	arxiv 1907.06484
Efficient Neural Architecture Transformation Searchin Channel-Level for Object Detection	Junran Peng, Ming Sun, Zhaoxiang Zhang	2019	arxiv 1909.02293
A Comparative Study of Confidence Calibration in Deep Learning: From Computer Vision to Medical Imaging	Riqiang Gao, Thomas Li, Yucheng Tang	2022	arxiv 2206.08833
Improving Long-tailed Object Detection with Image-Level Supervision by Multi-Task Collaborative Learning	Bo Li, Yongqiang Yao, Jingru Tan	2022	arxiv 2210.05568

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