Search Results for author: Tianyi Zhao

Found 8 papers, 1 papers with code

Deep Mixture of Diverse Experts for Large-Scale Visual Recognition

no code implementations24 Jun 2017 Tianyi Zhao, Jun Yu, Zhenzhong Kuang, Wei zhang, Jianping Fan

In this paper, a deep mixture of diverse experts algorithm is developed for seamlessly combining a set of base deep CNNs (convolutional neural networks) with diverse outputs (task spaces), e. g., such base deep CNNs are trained to recognize different subsets of tens of thousands of atomic object classes.

Multi-Task Learning Object +1

Embedding Visual Hierarchy with Deep Networks for Large-Scale Visual Recognition

no code implementations8 Jul 2017 Tianyi Zhao, Baopeng Zhang, Wei zhang, Ning Zhou, Jun Yu, Jianping Fan

Our LMM model can provide an end-to-end approach for jointly learning: (a) the deep networks to extract more discriminative deep features for image and object class representation; (b) the tree classifier for recognizing large numbers of object classes hierarchically; and (c) the visual hierarchy adaptation for achieving more accurate indexing of large numbers of object classes hierarchically.

Object Object Recognition

GAN-RXA: A Practical Scalable Solution to Receiver-Agnostic Transmitter Fingerprinting

no code implementations25 Mar 2023 Tianyi Zhao, Shamik Sarkar, Enes Krijestorac, Danijela Cabric

We also propose two deep-learning approaches (SD-RXA and GAN-RXA) in this first stage to improve the receiver-agnostic property of the RXA framework.

Outlier Detection

Learning to Pan-sharpening with Memories of Spatial Details

1 code implementation28 Jun 2023 Maoxun Yuan, Tianyi Zhao, Bo Li, Xingxing Wei

To address this issue, in this paper we observe that the spatial details from PAN images are mainly high-frequency cues, i. e., the edges reflect the contour of input PAN images.

Unveiling the Role of Message Passing in Dual-Privacy Preservation on GNNs

no code implementations25 Aug 2023 Tianyi Zhao, Hui Hu, Lu Cheng

Graph Neural Networks (GNNs) are powerful tools for learning representations on graphs, such as social networks.

Node Classification Privacy Preserving

Removal and Selection: Improving RGB-Infrared Object Detection via Coarse-to-Fine Fusion

no code implementations19 Jan 2024 Tianyi Zhao, Maoxun Yuan, Xingxing Wei

Specifically, following this perspective, we design a Redundant Spectrum Removal module to coarsely remove interfering information within each modality and a Dynamic Feature Selection module to finely select the desired features for feature fusion.

feature selection Object +3

A Survey on Safe Multi-Modal Learning System

no code implementations8 Feb 2024 Tianyi Zhao, Liangliang Zhang, Yao Ma, Lu Cheng

In the rapidly evolving landscape of artificial intelligence, multimodal learning systems (MMLS) have gained traction for their ability to process and integrate information from diverse modality inputs.

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