H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 30 Citations 4,892 249 World Ranking 8700 National Ranking 77

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Algorithm

Shang-Hong Lai mainly focuses on Artificial intelligence, Computer vision, Pattern recognition, Algorithm and Image processing. His research investigates the link between Artificial intelligence and topics such as Machine learning that cross with problems in Object detection. His research combines Artificial neural network and Computer vision.

His Principal component analysis, Image segmentation and Segmentation study in the realm of Pattern recognition interacts with subjects such as Scheme. The various areas that he examines in his Algorithm study include Real image and Mathematical optimization. His Image processing study incorporates themes from Algorithm design, Template matching, Graphics processing unit and Seam carving.

His most cited work include:

  • Fusing generic objectness and visual saliency for salient object detection (325 citations)
  • From co-saliency to co-segmentation: An efficient and fully unsupervised energy minimization model (178 citations)
  • Learning-Based Vertebra Detection and Iterative Normalized-Cut Segmentation for Spinal MRI (139 citations)

What are the main themes of his work throughout his whole career to date?

Shang-Hong Lai focuses on Artificial intelligence, Computer vision, Pattern recognition, Algorithm and Facial recognition system. His work in Feature extraction, Feature, Image, Face and Motion estimation is related to Artificial intelligence. His study in Pixel, Image processing, Segmentation, Optical flow and Face detection falls under the purview of Computer vision.

His research integrates issues of Real image, Template matching and Search algorithm in his study of Image processing. His studies in Pattern recognition integrate themes in fields like Object-class detection, Facial expression and Robustness. His Algorithm research includes themes of Linear system and Mathematical optimization.

He most often published in these fields:

  • Artificial intelligence (83.17%)
  • Computer vision (66.99%)
  • Pattern recognition (35.28%)

What were the highlights of his more recent work (between 2014-2021)?

  • Artificial intelligence (83.17%)
  • Computer vision (66.99%)
  • Pattern recognition (35.28%)

In recent papers he was focusing on the following fields of study:

His primary areas of study are Artificial intelligence, Computer vision, Pattern recognition, Image and Deep learning. Artificial intelligence and Detector are frequently intertwined in his study. His study in Computer vision is interdisciplinary in nature, drawing from both Robustness and Solid modeling.

His Pattern recognition research integrates issues from RGB color model, Fingerprint, Fingerprint recognition and Fingerprint. His Image study also includes fields such as

  • Object and related Advanced driver assistance systems, Real-time computing and Energy,
  • Natural language processing which connect with Subspace topology and Closed captioning. His Deep learning research includes elements of Spatial analysis, Representation, Pose and Position.

Between 2014 and 2021, his most popular works were:

  • AugGAN: Cross Domain Adaptation with GAN-based Data Augmentation (85 citations)
  • A Compact Deep Learning Model for Robust Facial Expression Recognition (60 citations)
  • Driver Drowsiness Detection via a Hierarchical Temporal Deep Belief Network (60 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Computer vision
  • Algorithm

His primary areas of investigation include Artificial intelligence, Pattern recognition, Computer vision, Feature extraction and Deep learning. His study in Object detection, Discriminative model, Matching, Image quality and Convolutional neural network falls within the category of Artificial intelligence. His Pattern recognition research is multidisciplinary, incorporating perspectives in Artificial neural network, Face and Feature.

His work in the fields of Computer vision, such as Augmented reality, intersects with other areas such as Process. The study incorporates disciplines such as Image segmentation, RANSAC, Image warping, Interpolation and CUDA in addition to Feature extraction. His Deep learning study which covers Facial recognition system that intersects with Hidden Markov model and Overfitting.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Fusing generic objectness and visual saliency for salient object detection

Kai-Yueh Chang;Tyng-Luh Liu;Hwann-Tzong Chen;Shang-Hong Lai.
international conference on computer vision (2011)

448 Citations

From co-saliency to co-segmentation: An efficient and fully unsupervised energy minimization model

Kai-Yueh Chang;Tyng-Luh Liu;Shang-Hong Lai.
computer vision and pattern recognition (2011)

233 Citations

Learning-Based Vertebra Detection and Iterative Normalized-Cut Segmentation for Spinal MRI

Szu-Hao Huang;Yi-Hong Chu;Shang-Hong Lai;C.L. Novak.
IEEE Transactions on Medical Imaging (2009)

197 Citations

Fast Template Matching Based on Normalized Cross Correlation With Adaptive Multilevel Winner Update

Shou-Der Wei;Shang-Hong Lai.
IEEE Transactions on Image Processing (2008)

182 Citations

A generalized depth estimation algorithm with a single image

Shang-Hong Lai;Chang-Wu Fu;Shyang Chang.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1992)

165 Citations

Reliable and Efficient Computation of Optical Flow

Shang-Hong Lai;Baba C. Vemuri.
International Journal of Computer Vision (1998)

142 Citations

AugGAN: Cross Domain Adaptation with GAN-based Data Augmentation

Sheng-Wei Huang;Che-Tsung Lin;Shu-Ping Chen;Yen-Yi Wu.
european conference on computer vision (2018)

128 Citations

A robust and efficient video stabilization algorithm

Hung-Chang Chang;Shang-Hong Lai;Kuang-Rong Lu.
international conference on multimedia and expo (2004)

115 Citations

Driver Drowsiness Detection via a Hierarchical Temporal Deep Belief Network

Ching-Hua Weng;Ying-Hsiu Lai;Shang-Hong Lai.
asian conference on computer vision (2016)

105 Citations

A robust real-time video stabilization algorithm

Hung-Chang Chang;Shang-Hong Lai;Kuang-Rong Lu.
Journal of Visual Communication and Image Representation (2006)

102 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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