Faen Zhang
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View article: Hyperbolic Space with Hierarchical Margin Boosts Fine-Grained Learning from Coarse Labels
Hyperbolic Space with Hierarchical Margin Boosts Fine-Grained Learning from Coarse Labels Open
Learning fine-grained embeddings from coarse labels is a challenging task due to limited label granularity supervision, i.e., lacking the detailed distinctions required for fine-grained tasks. The task becomes even more demanding when atte…
View article: Watch out Venomous Snake Species: A Solution to SnakeCLEF2023
Watch out Venomous Snake Species: A Solution to SnakeCLEF2023 Open
The SnakeCLEF2023 competition aims to the development of advanced algorithms for snake species identification through the analysis of images and accompanying metadata. This paper presents a method leveraging utilization of both images and …
View article: Dual Attention Networks for Few-Shot Fine-Grained Recognition
Dual Attention Networks for Few-Shot Fine-Grained Recognition Open
The task of few-shot fine-grained recognition is to classify images belonging to subordinate categories merely depending on few examples. Due to the fine-grained nature, it is desirable to capture subtle but discriminative part-level patte…
View article: Monotonic Neural Network: combining Deep Learning with Domain Knowledge for Chiller Plants Energy Optimization
Monotonic Neural Network: combining Deep Learning with Domain Knowledge for Chiller Plants Energy Optimization Open
In this paper, we are interested in building a domain knowledge based deep learning framework to solve the chiller plants energy optimization problems. Compared to the hotspot applications of deep learning (e.g. image classification and NL…
View article: Zero-Shot Instance Segmentation
Zero-Shot Instance Segmentation Open
Deep learning has significantly improved the precision of instance segmentation with abundant labeled data. However, in many areas like medical and manufacturing, collecting sufficient data is extremely hard and labeling this data requires…
View article: Deep Learning in the Era of Edge Computing: Challenges and Opportunities
Deep Learning in the Era of Edge Computing: Challenges and Opportunities Open
The era of edge computing has arrived. Although the Internet is the backbone of edge computing, its true value lies at the intersection of gathering data from sensors and extracting meaningful information from the sensor data. We envision …
View article: AinnoSeg: Panoramic Segmentation with High Perfomance
AinnoSeg: Panoramic Segmentation with High Perfomance Open
Panoramic segmentation is a scene where image segmentation tasks is more difficult. With the development of CNN networks, panoramic segmentation tasks have been sufficiently developed.However, the current panoramic segmentation algorithms …
View article: A fine-grained policy model for Provenance-based Access Control and Policy Algebras.pdf
A fine-grained policy model for Provenance-based Access Control and Policy Algebras.pdf Open
A fine-grained provenance-based access control policy model is proposed in this paper, in order to improve the express performance of existing model. This method employs provenance as conditions to determine whether a piece of data can be …
View article: Provenance-based Classification Policy based on Encrypted Search
Provenance-based Classification Policy based on Encrypted Search Open
As an important type of cloud data, digital provenance is arousing increasing attention on improving system performance. Currently, provenance has been employed to provide cues regarding access control and to estimate data quality. However…
View article: Regression via Arbitrary Quantile Modeling
Regression via Arbitrary Quantile Modeling Open
In the regression problem, L1 and L2 are the most commonly used loss functions, which produce mean predictions with different biases. However, the predictions are neither robust nor adequate enough since they only capture a few conditional…
View article: HM-NAS: Efficient Neural Architecture Search via Hierarchical Masking
HM-NAS: Efficient Neural Architecture Search via Hierarchical Masking Open
The use of automatic methods, often referred to as Neural Architecture Search (NAS), in designing neural network architectures has recently drawn considerable attention. In this work, we present an efficient NAS approach, named HM- NAS, th…
View article: Accurate Face Detection for High Performance
Accurate Face Detection for High Performance Open
Face detection has witnessed significant progress due to the advances of deep convolutional neural networks (CNNs). Its central issue in recent years is how to improve the detection performance of tiny faces. To this end, many recent works…
View article: Deep Residual Networks with a Fully Connected Recon-struction Layer for Single Image Super-Resolution
Deep Residual Networks with a Fully Connected Recon-struction Layer for Single Image Super-Resolution Open
Recently, deep neural networks have achieved impressive performance in terms of both reconstruction accuracy and efficiency for single image super-resolution (SISR). However, the network model of these methods is a fully convolutional neur…