Supervised ImageNet

October 5, 2024

RetCompletion:High-Speed Inference Image Completion with Retentive Network
Yueyang Cang, Pingge Hu, Xiaoteng Zhang, Xingtong Wang, Yuhang Liu, Li Shi
Supervised ImageNet Image Completion Retentive Network

October 2, 2024

DRUPI: Dataset Reduction Using Privileged Information
Shaobo Wang, Yantai Yang, Shuaiyu Zhang, Chenghao Sun, Weiya Li, Xuming Hu, Linfeng Zhang
Supervised ImageNet Privileged Information Data Reduction
Replacement Learning: Training Vision Tasks with Fewer Learnable Parameters
Yuming Zhang, Peizhe Wang, Shouxin Zhang, Dongzhi Guan, Jiabin Liu, Junhao Su
Deep Learning Model Supervised ImageNet Deeper Network End to End Training Trainable Parameter

September 28, 2024

Learning to Obstruct Few-Shot Image Classification over Restricted Classes
Amber Yijia Zheng, Chiao-An Yang, Raymond A. Yeh
LeArning Abstract Pre Trained Model Image Classification Supervised ImageNet Shot Classification Class Specific Pre Trained Backbone

September 16, 2024

InfoDisent: Explainability of Image Classification Models by Information Disentanglement
Łukasz Struski, Jacek Tabor
Pre Trained Model Supervised ImageNet High Explainability Image Classification Model Model Parameter Classification Network Pre Trained Neural Network

September 12, 2024

Reimagining Linear Probing: Kolmogorov-Arnold Networks in Transfer Learning
Sheng Shen, Rabih Younes
Transfer Learning Pre Trained Model Supervised ImageNet Kolmogorov Arnold Network Linear Probing

September 11, 2024

A Scalable Algorithm for Active Learning
Youguang Chen, Zheyu Wen, George Biros
Active Learning Supervised ImageNet Synthetic Dataset Multiclass Classification Scalable Algorithm ActIve Learning algORithm

September 10, 2024

Hierarchical Multi-Label Classification with Missing Information for Benthic Habitat Imagery
Isaac Xu, Benjamin Misiuk, Scott C. Lowe, Martin Gillis, Craig J. Brown, Thomas Trappenberg
Supervised ImageNet Hierarchical Multi Label Classification Seafloor Image

September 6, 2024

Efficient Training of Large Vision Models via Advanced Automated Progressive Learning
Changlin Li, Jiawei Zhang, Sihao Lin, Zongxin Yang, Junwei Liang, Xiaodan Liang, Xiaojun Chang
Vision Transformer Supervised ImageNet Real Time Efficient Training Large Vision Model Progressive Learning

August 31, 2024

August 30, 2024

Disease Classification and Impact of Pretrained Deep Convolution Neural Networks on Diverse Medical Imaging Datasets across Imaging Modalities
Jutika Borah, Kumaresh Sarmah, Hidam Kumarjit Singh
Global Impact Deep Convolutional Neural Network Supervised ImageNet Medical Image Datasets Disease Classification Pre Trained Convolutional Neural Network Imaging Modality Medical Imaging Task

August 28, 2024

NAS-BNN: Neural Architecture Search for Binary Neural Networks
Zhihao Lin, Yongtao Wang, Jinhe Zhang, Xiaojie Chu, Haibin Ling
Neural Architecture Search Supervised ImageNet Binary Neural Network Full Precision

August 23, 2024

Symmetric masking strategy enhances the performance of Masked Image Modeling
Khanh-Binh Nguyen, Chae Jung Park
Vision Transformer Supervised ImageNet System Performance Strategy Logic Masked Image Modeling Masking Strategy Random Masking

August 22, 2024

Enhanced Infield Agriculture with Interpretable Machine Learning Approaches for Crop Classification
Sudi Murindanyi, Joyce Nakatumba-Nabende, Rahman Sanya, Rose Nakibuule, Andrew Katumba
Image Classification Supervised ImageNet Model Explanation Field Robotics Crop Classification Interpretable Machine Learning Method

August 20, 2024

Breast tumor classification based on self-supervised contrastive learning from ultrasound videos
Yunxin Tang, Siyuan Tang, Jian Zhang, Hao Chen
Supervised ImageNet Self Supervised Contrastive Learning Breast Ultrasound Breast Cancer Classification Ultrasound Video

August 15, 2024

Navigating Data Scarcity using Foundation Models: A Benchmark of Few-Shot and Zero-Shot Learning Approaches in Medical Imaging
Stefano Woerner, Christian F. Baumgartner
New Benchmark Foundation Model Shot Learning Supervised ImageNet Medical Imaging Zero Shot Learning Medical Image Datasets Data Scarcity Medical Image Analysis Task Learning Approach

August 5, 2024

July 25, 2024

$\mathbb{X}$-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs
Vlad Sobal, Mark Ibrahim, Randall Balestriero, Vivien Cabannes, Diane Bouchacourt, Pietro Astolfi, Kyunghyun Cho, Yann LeCun
Contrastive Learning Supervised ImageNet Contrastive Loss Graph Sample

Papers

RetCompletion:High-Speed Inference Image Completion with Retentive Network

DRUPI: Dataset Reduction Using Privileged Information

Replacement Learning: Training Vision Tasks with Fewer Learnable Parameters

Learning to Obstruct Few-Shot Image Classification over Restricted Classes

InfoDisent: Explainability of Image Classification Models by Information Disentanglement

Reimagining Linear Probing: Kolmogorov-Arnold Networks in Transfer Learning

A Scalable Algorithm for Active Learning

Hierarchical Multi-Label Classification with Missing Information for Benthic Habitat Imagery

Efficient Training of Large Vision Models via Advanced Automated Progressive Learning

Data Augmentation for Image Classification using Generative AI

Ethical Challenges in Computer Vision: Ensuring Privacy and Mitigating Bias in Publicly Available Datasets

Disease Classification and Impact of Pretrained Deep Convolution Neural Networks on Diverse Medical Imaging Datasets across Imaging Modalities

NAS-BNN: Neural Architecture Search for Binary Neural Networks

Symmetric masking strategy enhances the performance of Masked Image Modeling

Enhanced Infield Agriculture with Interpretable Machine Learning Approaches for Crop Classification

Breast tumor classification based on self-supervised contrastive learning from ultrasound videos

Navigating Data Scarcity using Foundation Models: A Benchmark of Few-Shot and Zero-Shot Learning Approaches in Medical Imaging

LaMamba-Diff: Linear-Time High-Fidelity Diffusion Models Based on Local Attention and Mamba

Unsupervised Domain Adaption Harnessing Vision-Language Pre-training

$\mathbb{X}$-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs