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SPS Blog Article

Deep CNN-Based Channel Estimation Using 3D Channel Correlation

Peihao Dong

Millimeter wave (mmWave) communications provide a promising solution to meet the proliferating demand for high data rate because of large bandwidth. The current “boomingly” deployed fifth generation communication system (5G) has not actually touched the dominant frequency band of mmWave and thus can hardly enjoy its merit on dramatically boosting transmission rate, which motivates us to conduct research on the ultimate implementation of mmWave communications.

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Coarse-to-Fine CNN for Image Super-Resolution

Chunwei Tian, Yong Xu, Wangmeng Zuo, Bob Zhang, Lunke Fei, Chia-Wen Lin

A coarse-to-fine SR CNN (CFSRCNN) consisting of a stack of feature extraction blocks (FEBs), an enhancement block (EB), a construction block (CB) and, a feature refinement block (FRB) is proposed to learn a robust SR model.

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Collaborative Cloud and Edge Mobile Computing in C-RAN Systems

Seok-Hwan Park, Seongah Jeong, Jinyeop Na, Osvaldo Simeone, Shlomo Shamai

To handle the various types of tasks in the upcoming cellular services, we can design the system with both cloud and edge computing capabilities, where the computational tasks can be partially offloaded to the ENs and the CP.

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Revitalizing Underwater Image Enhancement in the Deep Learning Era

Dr. Chongyi Li

Underwater image enhancement has drawn considerable attention in both image processing and underwater vision. Due to the complicated underwater environment and lighting conditions, enhancing underwater image is a challenging problem. 

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10 Mar.

How can we make cameras smarter to better analyze humans?

Dr. Joe (Zhou) Ren

This blog describes 4 computer vision algorithms for better human analysis, that understand human hand, gesture, pose, and action from various input modalities.

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Deep-learning-based audio-visual speech enhancement

Dr. Daniel Michelsanti

We all experienced the discomfort of communicating with our friends at a cocktail party or in a pub with loud background music. When difficult acoustic scenarios like these occur, we tend to rely on several visual cues, such as lips and mouth movement of the speaker, in order to understand the speech of interest.

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PANNs: Large-scale Pretrained Audio Neural Networks for Audio Pattern Recognition

Dr. Qiuqiang Kong

Audio pattern recognition is an important research topic in the machine learning area, and includes several tasks such as audio tagging, acoustic scene classification, music classification, speech emotion classification and sound event detection. In this blog, we introduce pretrained audio neural networks (PANNs) trained on the large-scale AudioSet dataset. These PANNs are transferred to other audio related tasks. We investigate the performance and computational complexity of PANNs modeled by a variety of convolutional neural networks. We propose an architecture called Wavegram-Logmel-CNN using both log-mel spectrogram and waveform as input feature.

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Frontal-Centers Guided Face: Boosting Face Recognition by Learning Pose-Invariant Features

Yingfan Tao

Recent years, face recognition has made a remarkable breakthrough due to the emergence of deep learning. However, compared with frontal face recognition, many deep face recognition models still suffer serious performance degradation when handling profile faces. To address this issue, we propose a novel Frontal-Centers Guided Loss (FCGFace) to obtain highly discriminative features for face recognition. Most existing discriminative feature learning approaches project features from the same class into a separated latent subspace.

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Recent Advances of Deep Learning within X-ray Security Imaging

Dr. Samet Akcay

This blog explores modern deep learning applications as well as traditional machine learning techniques for automated X-ray security imaging.

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Reconfigurable Intelligent Surfaces Aided Robust Systems

Dr. Gui Zhou and Dr. Cunhua Pan

A framework of robust transmission design for reconfigurable intelligent surfaces (RIS) aided systems has been proposed to address the imperfect cascaded channel state information issue.

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