9 citations · 30 across the 8 of their papers we have counts for
8 papers
CAMotion: A High-Quality Benchmark for Camouflaged Moving Object Detection in the Wild
Siyuan Yao, Hao Sun, Ruiqi Yu +3
Discovering camouflaged objects is a challenging task in computer vision due to the high similarity between camouflaged objects and their surroundings. While the problem of camoufl…
RRR-Net: Reusing, Reducing, and Recycling a Deep Backbone Network
Haozhe Sun, Isabelle Guyon, Felix Mohr +1
It has become mainstream in computer vision and other machine learning domains to reuse backbone networks pre-trained on large datasets as preprocessors. Typically, the last layer…
Modularity in Deep Learning: A Survey
Haozhe Sun, Isabelle Guyon
Modularity is a general principle present in many fields. It offers attractive advantages, including, among others, ease of conceptualization, interpretability, scalability, module…
Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image Classification
Ihsan Ullah, Dustin Carrión-Ojeda, Sergio Escalera +7
We introduce Meta-Album, an image classification meta-dataset designed to facilitate few-shot learning, transfer learning, meta-learning, among other tasks. It includes 40 open dat…
Lessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification
Adrian El Baz, Ihsan Ullah, Edesio Alcobaça +17
Although deep neural networks are capable of achieving performance superior to humans on various tasks, they are notorious for requiring large amounts of data and computing resourc…
LTU Attacker for Membership Inference
Joseph Pedersen, Rafael Muñoz-Gómez, Jiangnan Huang +3
We address the problem of defending predictive models, such as machine learning classifiers (Defender models), against membership inference attacks, in both the black-box and white…
OmniPrint: A Configurable Printed Character Synthesizer
Haozhe Sun, Wei-Wei Tu, Isabelle Guyon
We introduce OmniPrint, a synthetic data generator of isolated printed characters, geared toward machine learning research. It draws inspiration from famous datasets such as MNIST,…
Effectiveness of Optimization Algorithms in Deep Image Classification
Zhaoyang Zhu, Haozhe Sun, Chi Zhang
Adam is applied widely to train neural networks. Different kinds of Adam methods with different features pop out. Recently two new adam optimizers, AdaBelief and Padam are introduc…