research
∙
04/25/2023
Bayesian Optimization Meets Self-Distillation
Bayesian optimization (BO) has contributed greatly to improving model pe...
share
research
∙
03/23/2023
OCELOT: Overlapped Cell on Tissue Dataset for Histopathology
Cell detection is a fundamental task in computational pathology that can...
research
∙
12/09/2022
Benchmarking Self-Supervised Learning on Diverse Pathology Datasets
Computational pathology can lead to saving human lives, but models are a...
research
∙
09/26/2022
Improving Multi-fidelity Optimization with a Recurring Learning Rate for Hyperparameter Tuning
Despite the evolution of Convolutional Neural Networks (CNNs), their per...
research
∙
03/29/2022
Interactive Multi-Class Tiny-Object Detection
Annotating tens or hundreds of tiny objects in a given image is laboriou...
research
∙
07/15/2020
Learning Visual Context by Comparison
Finding diseases from an X-ray image is an important yet highly challeng...
research
∙
10/25/2019
Reducing Domain Gap via Style-Agnostic Networks
Deep learning models often fail to maintain their performance on new tes...
research
∙
09/16/2019
Visuomotor Understanding for Representation Learning of Driving Scenes
Dashboard cameras capture a tremendous amount of driving scene video eac...
research
∙
06/07/2019
PseudoEdgeNet: Nuclei Segmentation only with Point Annotations
Nuclei segmentation is one of the important tasks for whole slide image ...
research
∙
05/09/2019
Learning Loss for Active Learning
The performance of deep neural networks improves with more annotated dat...
research
∙
04/12/2018
Distort-and-Recover: Color Enhancement using Deep Reinforcement Learning
Learning-based color enhancement approaches typically learn to map from ...
research
∙
02/06/2018
Learning Image Representations by Completing Damaged Jigsaw Puzzles
In this paper, we explore methods of complicating self-supervised tasks ...
research
∙
08/07/2017
Two-Phase Learning for Weakly Supervised Object Localization
Weakly supervised semantic segmentation and localiza- tion have a proble...
research
∙
12/20/2016
Action-Driven Object Detection with Top-Down Visual Attentions
A dominant paradigm for deep learning based object detection relies on a...
research
∙
03/24/2016
Pixel-Level Domain Transfer
We present an image-conditional image generation model. The model transf...
research
∙
06/25/2015
AttentionNet: Aggregating Weak Directions for Accurate Object Detection
We present a novel detection method using a deep convolutional neural ne...
research
∙
12/04/2014
