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- Honghai LiuSuggested from co-authorship
- David J BrownSuggested from co-authorship
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Works228 from public data
- Getting to know low-light images with the Exclusively Dark dataset901
It is found that the effects of low-light reaches far deeper into the features than can be solved by simple "illumination invariance'", and it is hoped that this analysis and the Exclusively Dark dataset can encourage the growth in low-lights domain researches on different fields.
- How deep learning extracts and learns leaf features for plant classification575
This paper learns useful leaf features directly from the raw representations of input data using Convolutional Neural Networks (CNN), and gains intuition of the chosen features based on a Deconvolutional Network (DN) approach, and gains insights into the design of new hybrid feature extraction models which are able to further improve the discriminative power of plant classification systems.
- Total-Text: A Comprehensive Dataset for Scene Text Detection and Recognition571
To evaluate its robustness against curved text, DeconvNet is fine-tuned and benchmarked on Total-Text to facilitate a new research direction for the scene text community.
- A robust arbitrary text detection system for natural scene images562
A robust system based on the concepts of Mutual Direction Symmetry (MDS), Mutual Magnitude Symmetric (MMS) and Gradient Vector Symmeter (GVS) properties to identify text pixel candidates regardless of any orientations including curves from natural scene images is presented.
- Deep-plant: Plant identification with convolutional neural networks487
Experimental results using these CNN features with different classifiers show consistency and superiority compared to the state-of-the art solutions which rely on hand-crafted features.
- Automated Detection and Classification of Oral Lesions Using Deep Learning for Early Detection of Oral Cancer372
Two deep learning based computer vision approaches were assessed for the automated detection and classification of oral lesions for the early detection of oral cancer, these were image classification with ResNet-101 and object detection with the Faster R-CNN.
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- ICDAR2019 Robust Reading Challenge on Arbitrary-Shaped Text - RRC-ArT272
This paper reports the ICDAR2019 Robust Reading Challenge on Arbitrary-Shaped Text - RRC-ArT that consists of three major challenges: i) scene text detection, ii) sceneText recognition, and iii) scenetext spotting.
- 254
- ICDAR 2019 Competition on Large-Scale Street View Text with Partial Labeling - RRC-LSVT207
This competition aims to explore the abilities of state-of-the-art methods to detect and recognize text instances from large-scale street view images, closing gaps between research benchmarks and real applications.
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- A Fusion Approach for Efficient Human Skin Detection188
An eye detector is used to refine the skin model for a specific person and a smoothed 2-D histogram and Gaussian model is combined, for automatic human skin detection in color image(s).
- 177
- Total-Text: toward orientation robustness in scene text detection154
A new scene text detection model is proposed as the baseline for Total-Text, namely Polygon-Faster-RCNN, and its ability to detect text of all orientations is demonstrated.
- Crowd behavior analysis: A review where physics meets biology152
A review of the state-of-the-art methods in crowd behavior analysis from the physics and biologically inspired perspectives is provided, providing insights and comprehensive discussions for a broader understanding of the underlying prospect of blending physics and biology studies in computer vision.
- Deep Polarized Network for Supervised Learning of Accurate Binary Hashing Codes148
A novel deep polarized network (DPN) for learning to hash is proposed, in which each channel in the network outputs is pushed far away from zero by employing a differentiable bit-wise hinge-like loss which is dubbed as polarization loss.
- 146
- On the General Value of Evidence, and Bilingual Scene-Text Visual Question Answering132
A dataset that takes a step towards addressing the VQA problem in that it contains questions expressed in two languages, and an evaluation process that co-opts a well understood image-based metric to reflect the method’s ability to reason.
- ArtGAN: Artwork synthesis with conditional categorical GANs130
The proposed ArtGAN is capable to create realistic artwork, as well as generate compelling real world images that globally look natural with clear shape on CIFAR-10.
- ArtGAN: Artwork Synthesis with Conditional Categorial GANs.127
The proposed ArtGAN is capable to create realistic artwork, as well as generate compelling real world images that globally look natural with clear shape on CIFAR-10.
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- Multi-Organ Plant Classification Based on Convolutional and Recurrent Neural Networks117
A hybrid generic-organ convolutional neural network (HGO-CNN) is introduced, which takes into account both organ and generic information, combining them using a new feature fusion scheme for species classification.
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- Fuzzy human motion analysis: A review92
The fuzzy set oriented approaches for HMA are reviewed, individuating how the fuzzy set may improve the HMA, envisaging and delineating the future perspectives and ideas for future research are discussed.
Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-14. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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