Search Results for author: Yu Cai

Found 10 papers, 6 papers with code

MedIAnomaly: A comparative study of anomaly detection in medical images

1 code implementation6 Apr 2024 Yu Cai, Weiwen Zhang, Hao Chen, Kwang-Ting Cheng

Anomaly detection (AD) aims at detecting abnormal samples that deviate from the expected normal patterns.

Anomaly Classification Anomaly Detection +2

Rethinking Autoencoders for Medical Anomaly Detection from A Theoretical Perspective

no code implementations14 Mar 2024 Yu Cai, Hao Chen, Kwang-Ting Cheng

To the best of our knowledge, this is the first effort to theoretically clarify the principles and design philosophy of AE for anomaly detection.

Anomaly Detection Philosophy

Self-Supervised Depth Completion Guided by 3D Perception and Geometry Consistency

no code implementations23 Dec 2023 Yu Cai, Tianyu Shen, Shi-Sheng Huang, Hua Huang

Depth completion, aiming to predict dense depth maps from sparse depth measurements, plays a crucial role in many computer vision related applications.

Depth Completion

Dual-distribution discrepancy with self-supervised refinement for anomaly detection in medical images

1 code implementation9 Oct 2022 Yu Cai, Hao Chen, Xin Yang, Yu Zhou, Kwang-Ting Cheng

Due to the high-cost annotations of abnormal images, most methods utilize only known normal images during training and identify samples deviating from the normal profile as anomalies in the testing phase.

Anomaly Detection Self-Supervised Learning

Dual-Distribution Discrepancy for Anomaly Detection in Chest X-Rays

1 code implementation8 Jun 2022 Yu Cai, Hao Chen, Xin Yang, Yu Zhou, Kwang-Ting Cheng

Subsequently, inter-discrepancy between the two modules, and intra-discrepancy inside the module that is trained on only normal images are designed as anomaly scores to indicate anomalies.

One-Class Classification

Fast semidefinite programming with feedforward neural networks

no code implementations11 Nov 2020 Tamás Kriváchy, Yu Cai, Joseph Bowles, Daniel Cavalcanti, Nicolas Brunner

Given the optimization constraints as an input, a neural network outputs values for the optimization parameters such that the constraints are satisfied, both for the primal and the dual formulations of the task.

A neural network oracle for quantum nonlocality problems in networks

1 code implementation24 Jul 2019 Tamás Kriváchy, Yu Cai, Daniel Cavalcanti, Arash Tavakoli, Nicolas Gisin, Nicolas Brunner

As such, the neural network acts as an oracle, demonstrating that a behavior is classical if it can be learned.

Causal Inference

Experimental many-pairs nonlocality

1 code implementation4 Apr 2017 Hou Shun Poh, Alessandro Cerè, Jean-Daniel Bancal, Yu Cai, Nicolas Sangouard, Valerio Scarani, Christian Kurtsiefer

Collective measurements on large quantum systems together with a majority voting strategy can lead to a violation of the CHSH Bell inequality.

Quantum Physics

Sparse Coding and Counting for Robust Visual Tracking

no code implementations28 May 2016 Risheng Liu, Jing Wang, Yiyang Wang, Zhixun Su, Yu Cai

In this paper, we propose a novel sparse coding and counting method under Bayesian framwork for visual tracking.

Visual Tracking

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