Which affiliation has fewer publications cited by count, University of Twente or Qualcomm (United Kingdom)?
Qualcomm (United Kingdom)
Xin Yu and Fatih Porikli: Imagining the Unimaginable Faces by Deconvolutional Networks. (2018) authored by Fatih Porikli. Jie Ni et al.: Detecting 3D geometric boundaries of indoor scenes under varying lighting. (2014) authored by Fatih Porikli. Rui Zhu et al.: Dense Vision Transformers for Single-Image Inverse Rendering in Indoor Scenes. (2022) authored by Fat Fatih Porikli and Jay Thornton: Shadow Flow: A Recursive Method to Learn Moving Cast Shadows. (2018) authored by Fatih Porikli. Rui Zhu et al.: IRISformer: Dense Vision Transformers for Single-Image Inverse Rendering in Indoor Scenes. Fatih Porikli and Yao Wang: Constrained video object segmentation by color masks and MPEG-7 descriptors. (2002) authored by Fatih Porikli. Muzammal Naseer et al.: Stylized Adversarial Defense. (2020) authored by Fatih Porikli. Haoyang Zhang et al.: Learning Spatial Transforms for Refining Object Segment Proposals. (2017) authored by Fat Fatih Porikli and Ajay J. Joshi: Neural Mesh Fusion: Unsupervised 3D Planar Surface Understanding. (2016) authored by Fatih Porikli. Jing Zhang et al.: Deep Salient Object Detection by Integrating Multi-level Cues. (2017) authored by Fatih Porikli. Jing Zhang et al.: Multi-scale salient object detection with pyramid spatial pooling. (2017) authored by Fatih Porikli. Hanzhe Hu et al.: Learning Implicit Feature Alignment Function for Semantic Segmentation. (2022) authored by Fatih Porikli. Babak Ehteshami Bejnordi et al.: SALISA: Saliency-Based Input Sampling for Efficient Video Object Detection. (2022) authored by Fatih Porikli. Shubhankar Borse et al.: DejaVu: Conditional Regenerative Learning to Enhance Dense Prediction. (2017) authored by Fatih Porikli. Fatih Porikli was named a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) in 2014 for his contributions to computer vision and video surveillance. He is the author of Gao Zhu et al.: Tracking Randomly Moving Objects on Edge Box Proposals. (2015).
[INST]
Utilize the provided context information, to generate answers to the following question: 
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Question: Which affiliation has fewer publications cited by count, University of Twente or Qualcomm (United Kingdom)?
Context: Xin Yu and Fatih Porikli: Imagining the Unimaginable Faces by Deconvolutional Networks. (2018) authored by Fatih Porikli. Jie Ni et al.: Detecting 3D geometric boundaries of indoor scenes under varying lighting. (2014) authored by Fatih Porikli. Rui Zhu et al.: Dense Vision Transformers for Single-Image Inverse Rendering in Indoor Scenes. (2022) authored by Fat Fatih Porikli and Jay Thornton: Shadow Flow: A Recursive Method to Learn Moving Cast Shadows. (2018) authored by Fatih Porikli. Rui Zhu et al.: IRISformer: Dense Vision Transformers for Single-Image Inverse Rendering in Indoor Scenes. Fatih Porikli and Yao Wang: Constrained video object segmentation by color masks and MPEG-7 descriptors. (2002) authored by Fatih Porikli. Muzammal Naseer et al.: Stylized Adversarial Defense. (2020) authored by Fatih Porikli. Haoyang Zhang et al.: Learning Spatial Transforms for Refining Object Segment Proposals. (2017) authored by Fat Fatih Porikli and Ajay J. Joshi: Neural Mesh Fusion: Unsupervised 3D Planar Surface Understanding. (2016) authored by Fatih Porikli. Jing Zhang et al.: Deep Salient Object Detection by Integrating Multi-level Cues. (2017) authored by Fatih Porikli. Jing Zhang et al.: Multi-scale salient object detection with pyramid spatial pooling. (2017) authored by Fatih Porikli. Hanzhe Hu et al.: Learning Implicit Feature Alignment Function for Semantic Segmentation. (2022) authored by Fatih Porikli. Babak Ehteshami Bejnordi et al.: SALISA: Saliency-Based Input Sampling for Efficient Video Object Detection. (2022) authored by Fatih Porikli. Shubhankar Borse et al.: DejaVu: Conditional Regenerative Learning to Enhance Dense Prediction. (2017) authored by Fatih Porikli. Fatih Porikli was named a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) in 2014 for his contributions to computer vision and video surveillance. He is the author of Gao Zhu et al.: Tracking Randomly Moving Objects on Edge Box Proposals. (2015).
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