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- Implicit Dual-Domain Convolutional Network for Robust Color Image Compression Artifact Reduction106
An implicit dual-domain convolutional network with a pixel position labeling map and quantization tables as inputs is proposed and is superior to the state-of-the-art methods and IDCN-f exhibits excellent abilities to handle a wide range of compression qualities with a little trade-off against performance.
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- AIM 2019 Challenge on Image Demoireing: Methods and Results57
This paper reviews the first-ever image demoireing challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ICCV 2019, and focuses on the proposed solutions and their results.
- Pneumonia Detection Using an Improved Algorithm Based on Faster R-CNN49
An improved algorithm that can provide doctors with location information of pneumonia lesions is proposed and obtained 39.23% Mean Average Precision on the X-ray image dataset from the Radiological Society of North America (RSNA) and got 38.02% mean average precision on the ChestX-ray14 dataset, surpassing other detection algorithms.
- A Cascade Face Spoofing Detector Based on Face Anti-Spoofing R-CNN and Improved Retinex LBP48
This paper designs face anti-spoofing region-based convolutional neural network (FARCNN), based on improved Faster region- based Convolutional Neural Network (R-CNN) framework, which is motivated by face detection and regards the face spoofing detection as a three-way classification to distinguish real face, fake face and background.
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- An Improved Algorithm for Detecting Pneumonia Based on YOLOv335
This study proposes an improved algorithm that can provide doctors with location information on lesions for the detection of pneumonia and obtained 46.84 mean average precision on the X-ray image dataset provided by the Radiological Society of North America (RSNA), surpassing other detection algorithms.
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- Field-programmable gate array implementation of a probabilistic neural network for motor cortical decoding in rats35
A field-programmable gate array (FPGA) implementation of a probabilistic neural network (PNN) is proposed and developed to decode motor cortical ensemble recordings in rats performing a lever-pressing task for water rewards, indicating that the performance of current FPGAs is competent for portable BMI applications.
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- S-Net: a scalable convolutional neural network for JPEG compression artifact reduction25
Experimental results indicate that the proposed S-Net CNN outperforms other CNN-based methods and achieves state-of-the-art performance.
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- Fast transcoding from H.264 to HEVC based on region feature analysis21
A fast H.264 to HEVC transcoding algorithm based on region feature analysis achieves a significant improvement on transcoding speed, while maintaining high Rate-Distortion performance.
- Dynamic DNN Decomposition for Lossless Synergistic Inference19
D, a dynamic DNN decomposition system for synergistic inference without precision loss is proposed, which introduces a heuristic algorithm named horizontal partition algorithm to split a DNN into three parts and can partially adjust the partitions at run time according to processing time and network conditions.
- GeminiNet: Combine Fully Convolution Network With Structure of Receptive Fields for Object Detection15
This article designs GeminiNet to identify and localize the pneumonia in Chest X-ray (CXR) images using a popular fully convolution architecture with computation shared on the entire image, combining RoI Align and PSRoI Pooling to capture global and local information and output.
- Robust visual tracking for planar objects using gradient orientation pyramid15
A robust DVT method, named gradient orientation pyramid efficient second-order minimization (GOP-ESM), based on the proposed gradient orientation Pyramid descriptor is presented, which outperforms the state-of-the-art tracking methods against various environmental variations, especially illumination changes.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-15. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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