Search Results for author: Peng Zhou

Found 27 papers, 12 papers with code

An Improved Reinforcement Learning Model Based on Sentiment Analysis

no code implementations19 Nov 2021 Yizhuo Li, Peng Zhou, Fangyi Li, Xiao Yang

The authors combined the deep Q network in reinforcement learning with the sentiment quantitative indicator ARBR to build a high-frequency stock trading model for the share market.

Sentiment Analysis

Prediction of Fund Net Value Based on ARIMA-LSTM Hybrid Model

no code implementations19 Nov 2021 Peng Zhou, Fangyi Li

The net value of the fund is affected by performance and market, and the researchers try to quantify these effects to predict the future net value by establishing different models.

Improved Method of Stock Trading under Reinforcement Learning Based on DRQN and Sentiment Indicators ARBR

no code implementations19 Nov 2021 Peng Zhou, Jingling Tang

With the application of artificial intelligence in the financial field, quantitative trading is considered to be profitable.

CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel Synthesis

1 code implementation19 Oct 2021 Peng Zhou, Lingxi Xie, Bingbing Ni, Qi Tian

The style-based GAN (StyleGAN) architecture achieved state-of-the-art results for generating high-quality images, but it lacks explicit and precise control over camera poses.

3D-Aware Image Synthesis Transfer Learning

Frustrated Arrays of Nanomagnets for Efficient Reservoir Computing

no code implementations16 Mar 2021 Alexander J. Edwards, Dhritiman Bhattacharya, Peng Zhou, Nathan R. McDonald, Lisa Loomis, Clare D. Thiem, Jayasimha Atulasimha, Joseph S. Friedman

We simulated our nanomagnet reservoir computer (NMRC) design on benchmark tasks, demonstrating NMRC's high memory content and expressibility.

Deep Video Inpainting Detection

no code implementations26 Jan 2021 Peng Zhou, Ning Yu, Zuxuan Wu, Larry S. Davis, Abhinav Shrivastava, Ser-Nam Lim

This paper studies video inpainting detection, which localizes an inpainted region in a video both spatially and temporally.

Video Inpainting

Omni-GAN: On the Secrets of cGANs and Beyond

1 code implementation ICCV 2021 Peng Zhou, Lingxi Xie, Bingbing Ni, Cong Geng, Qi Tian

The conditional generative adversarial network (cGAN) is a powerful tool of generating high-quality images, but existing approaches mostly suffer unsatisfying performance or the risk of mode collapse.

Conditional Image Generation

Searching towards Class-Aware Generators for Conditional Generative Adversarial Networks

1 code implementation25 Jun 2020 Peng Zhou, Lingxi Xie, Xiaopeng Zhang, Bingbing Ni, Qi Tian

To learn the sampling policy, a Markov decision process is embedded into the search algorithm and a moving average is applied for better stability.

Image Generation

Deepstrip: High-Resolution Boundary Refinement

no code implementations CVPR 2020 Peng Zhou, Brian Price, Scott Cohen, Gregg Wilensky, Larry S. Davis

In this paper, we target refining the boundaries in high resolution images given low resolution masks.

Occlusion-Adaptive Deep Network for Robust Facial Expression Recognition

no code implementations12 May 2020 Hui Ding, Peng Zhou, Rama Chellappa

Recognizing the expressions of partially occluded faces is a challenging computer vision problem.

Facial Expression Recognition

Inclusive GAN: Improving Data and Minority Coverage in Generative Models

1 code implementation ECCV 2020 Ning Yu, Ke Li, Peng Zhou, Jitendra Malik, Larry Davis, Mario Fritz

Generative Adversarial Networks (GANs) have brought about rapid progress towards generating photorealistic images.

DeepStrip: High Resolution Boundary Refinement

no code implementations25 Mar 2020 Peng Zhou, Brian Price, Scott Cohen, Gregg Wilensky, Larry S. Davis

In this paper, we target refining the boundaries in high resolution images given low resolution masks.

Reservoir Computing with Planar Nanomagnet Arrays

no code implementations24 Mar 2020 Peng Zhou, Nathan R. McDonald, Alexander J. Edwards, Lisa Loomis, Clare D. Thiem, Joseph S. Friedman

Reservoir computing is an emerging methodology for neuromorphic computing that is especially well-suited for hardware implementations in size, weight, and power (SWaP) constrained environments.

Wasserstein-Bounded Generative Adversarial Networks

no code implementations ICLR 2020 Peng Zhou, Bingbing Ni, Lingxi Xie, Xiaopeng Zhang, Hang Wang, Cong Geng, Qi Tian

In the field of Generative Adversarial Networks (GANs), how to design a stable training strategy remains an open problem.

Revisiting Image Aesthetic Assessment via Self-Supervised Feature Learning

no code implementations26 Nov 2019 Kekai Sheng, Wei-Ming Dong, Menglei Chai, Guohui Wang, Peng Zhou, Feiyue Huang, Bao-Gang Hu, Rongrong Ji, Chongyang Ma

In this paper, we revisit the problem of image aesthetic assessment from the self-supervised feature learning perspective.

K-BERT: Enabling Language Representation with Knowledge Graph

1 code implementation arXiv 2019 Weijie Liu, Peng Zhou, Zhe Zhao, Zhiruo Wang, Qi Ju, Haotang Deng, Ping Wang

For machines to achieve this capability, we propose a knowledge-enabled language representation model (K-BERT) with knowledge graphs (KGs), in which triples are injected into the sentences as domain knowledge.

Knowledge Graphs

Sionnx: Automatic Unit Test Generator for ONNX Conformance

1 code implementation12 Jun 2019 Xinli Cai, Peng Zhou, Shuhan Ding, Guoyang Chen, Weifeng Zhang

Finally, through this easy-to-use specification language, we are able to build a full testing specification which leverages LLVM TableGen to automatically generate unit tests for ONNX operators with much large coverage.

M2KD: Multi-model and Multi-level Knowledge Distillation for Incremental Learning

no code implementations3 Apr 2019 Peng Zhou, Long Mai, Jianming Zhang, Ning Xu, Zuxuan Wu, Larry S. Davis

Instead of sequentially distilling knowledge only from the last model, we directly leverage all previous model snapshots.

Incremental Learning Knowledge Distillation

Generate, Segment and Refine: Towards Generic Manipulation Segmentation

1 code implementation24 Nov 2018 Peng Zhou, Bor-Chun Chen, Xintong Han, Mahyar Najibi, Abhinav Shrivastava, Ser Nam Lim, Larry S. Davis

The advent of image sharing platforms and the easy availability of advanced photo editing software have resulted in a large quantities of manipulated images being shared on the internet.

Detecting Image Manipulation Image Generation +3

Pose Transferrable Person Re-Identification

no code implementations CVPR 2018 Jinxian Liu, Bingbing Ni, Yichao Yan, Peng Zhou, Shuo Cheng, Jianguo Hu

On the other hand, in addition to the conventional discriminator of GAN (i. e., to distinguish between REAL/FAKE samples), we propose a novel guider sub-network which encourages the generated sample (i. e., with novel pose) towards better satisfying the ReID loss (i. e., cross-entropy ReID loss, triplet ReID loss).

Person Re-Identification

Learning Rich Features for Image Manipulation Detection

2 code implementations CVPR 2018 Peng Zhou, Xintong Han, Vlad I. Morariu, Larry S. Davis

Image manipulation detection is different from traditional semantic object detection because it pays more attention to tampering artifacts than to image content, which suggests that richer features need to be learned.

Image Manipulation Image Manipulation Detection +1

Text Classification Improved by Integrating Bidirectional LSTM with Two-dimensional Max Pooling

3 code implementations COLING 2016 Peng Zhou, Zhenyu Qi, Suncong Zheng, Jiaming Xu, Hongyun Bao, Bo Xu

To integrate the features on both dimensions of the matrix, this paper explores applying 2D max pooling operation to obtain a fixed-length representation of the text.

Classification General Classification +2

Cannot find the paper you are looking for? You can Submit a new open access paper.