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IEEE Signal Processing Society Blog

The SPS blog aims to raise awareness about signal processing and Society-related topics to a general interest audience in an engaging, informal, and non-technical way. If you're interested in contributing to the SPS blog, please contact the SPS Blog Team at for more information.

Unlocking Real-Time 3D Imaging with Single-Photon LiDAR in Challenging Environments

Dr. Abderrahim Halimi

Our method overcomes 3D underwater imaging challenges by offering high-frame-rate video 3D imaging (>100 fps), providing uncertainty measures for estimates, and extending applicability to various obscurant media imaging.

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

Dr. Qiuqiang Kong

Pretrained audio neural networks (PANNs) are trained on 5800 hours of AudioSet data that can be used to recognize hundreds of sound types in the natural world.

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Deep Learning for All-in-Focus Imaging

Dr. Qian Huang

Focus stacking is an effective approach to extending the depth of field of a camera, yet is challenging with regard to 1) controlling focal planes in forming a stack and 2) fusing the focal stack into composites free from defocusing, i.e., all-in-focus. We propose a deep learning all-in-focus imaging pipeline as a novel solution for focus stacking.

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Underwater Image Enhancement via a Fast yet Effective Traditional Method

Weidong Zhang, Peixian Zhuang, Hai-Han Sun, Guohou Li, Sam Kwong, Chongyi Li

Addressing underwater image challenges, our method MLLE enhances color, contrast, and details efficiently. Outperforming competitors, it processes 1024×1024×3 images in under 1s on a single CPU. Experiments show improved underwater image segmentation, keypoint detection, and saliency detection.

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An Echo in Time: Tracing the Evolution of Beamforming Algorithms

Ahmet M. Elbir, Kumar Vijay Mishra, Sergiy A. Vorobyov, and Robert W. Heath, Jr.

Beamforming is a widely used signal processing technique to steer, shape, and focus an electromagnetic wave using an array of sensors toward a desired direction.

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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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