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.
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.
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
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.
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)
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)
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)
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)
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)
Reliable and Efficient Computation of Optical Flow
Shang-Hong Lai;Baba C. Vemuri.
International Journal of Computer Vision (1998)
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)
A robust and efficient video stabilization algorithm
Hung-Chang Chang;Shang-Hong Lai;Kuang-Rong Lu.
international conference on multimedia and expo (2004)
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)
A robust real-time video stabilization algorithm
Hung-Chang Chang;Shang-Hong Lai;Kuang-Rong Lu.
Journal of Visual Communication and Image Representation (2006)
Profile was last updated on December 6th, 2021.
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