Search Results for author: Minkyu Choi

Found 7 papers, 1 papers with code

Human Eyes Inspired Recurrent Neural Networks are More Robust Against Adversarial Noises

1 code implementation15 Jun 2022 Minkyu Choi, Yizhen Zhang, Kuan Han, Xiaokai Wang, Zhongming Liu

Compared to human vision, computer vision based on convolutional neural networks (CNN) are more vulnerable to adversarial noises.


Explainable Semantic Space by Grounding Language to Vision with Cross-Modal Contrastive Learning

no code implementations NeurIPS 2021 Yizhen Zhang, Minkyu Choi, Kuan Han, Zhongming Liu

After training, the language stream of this model is a stand-alone language model capable of embedding concepts in a visually grounded semantic space.

Contrastive Learning Image Retrieval +2

Generating Goal-Directed Visuomotor Plans Based on Learning Using a Predictive Coding-type Deep Visuomotor Recurrent Neural Network Model

no code implementations7 Mar 2018 Minkyu Choi, Takazumi Matsumoto, Minju Jung, Jun Tani

The current paper presents how a predictive coding type deep recurrent neural networks can generate vision-based goal-directed plans based on prior learning experience by examining experiment results using a real arm robot.

Predictive Coding for Dynamic Visual Processing: Development of Functional Hierarchy in a Multiple Spatio-Temporal Scales RNN Model

no code implementations2 Aug 2017 Minkyu Choi, Jun Tani

The paper examines how model performance during pattern generation as well as predictive imitation varies depending on the stage of learning.

Predictive Coding-based Deep Dynamic Neural Network for Visuomotor Learning

no code implementations8 Jun 2017 Jungsik Hwang, Jinhyung Kim, Ahmadreza Ahmadi, Minkyu Choi, Jun Tani

This study presents a dynamic neural network model based on the predictive coding framework for perceiving and predicting the dynamic visuo-proprioceptive patterns.

Action Generation

Predictive Coding for Dynamic Vision : Development of Functional Hierarchy in a Multiple Spatio-Temporal Scales RNN Model

no code implementations6 Jun 2016 Minkyu Choi, Jun Tani

The current paper presents a novel recurrent neural network model, the predictive multiple spatio-temporal scales RNN (P-MSTRNN), which can generate as well as recognize dynamic visual patterns in the predictive coding framework.

Achieving Synergy in Cognitive Behavior of Humanoids via Deep Learning of Dynamic Visuo-Motor-Attentional Coordination

no code implementations9 Jul 2015 Jungsik Hwang, Minju Jung, Naveen Madapana, Jinhyung Kim, Minkyu Choi, Jun Tani

The current study examines how adequate coordination among different cognitive processes including visual recognition, attention switching, action preparation and generation can be developed via learning of robots by introducing a novel model, the Visuo-Motor Deep Dynamic Neural Network (VMDNN).

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