Pyramid (geometry)
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Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation Open
Spatial pyramid pooling module or encode-decoder structure are used in deep neural networks for semantic segmentation task. The former networks are able to encode multi-scale contextual information by probing the incoming features with fil…
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New evidence pyramid Open
A pyramid has expressed the idea of hierarchy of medical evidence for so long, that not all evidence is the same. Systematic reviews and meta-analyses have been placed at the top of this pyramid for several good reasons. However, there are…
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M2Det: A Single-Shot Object Detector Based on Multi-Level Feature Pyramid Network Open
Feature pyramids are widely exploited by both the state-of-the-art one-stage object detectors (e.g., DSSD, RetinaNet, RefineDet) and the two-stage object detectors (e.g., Mask RCNN, DetNet) to alleviate the problem arising from scale varia…
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Deep Pyramid Convolutional Neural Networks for Text Categorization Open
This paper proposes a low-complexity word-level deep convolutional neural network (CNN) architecture for text categorization that can efficiently represent long-range associations in text. In the literature, several deep and complex neural…
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Automatic Ship Detection in Remote Sensing Images from Google Earth of Complex Scenes Based on Multiscale Rotation Dense Feature Pyramid Networks Open
Ship detection has been playing a significant role in the field of remote sensing for a long time, but it is still full of challenges. The main limitations of traditional ship detection methods usually lie in the complexity of application …
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EfficientDet: Scalable and Efficient Object Detection Open
Model efficiency has become increasingly important in computer vision. In this paper, we systematically study neural network architecture design choices for object detection and propose several key optimizations to improve efficiency. Firs…
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Learning Spatial Fusion for Single-Shot Object Detection Open
Pyramidal feature representation is the common practice to address the challenge of scale variation in object detection. However, the inconsistency across different feature scales is a primary limitation for the single-shot detectors based…
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Feature Pyramid Networks for Object Detection Open
Feature pyramids are a basic component in recognition systems for detecting objects at different scales. But recent deep learning object detectors have avoided pyramid representations, in part because they are compute and memory intensive.…
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Horizontal Pyramid Matching for Person Re-Identification Open
Despite the remarkable progress in person re-identification (Re-ID), such approaches still suffer from the failure cases where the discriminative body parts are missing. To mitigate this type of failure, we propose a simple yet effective H…
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Searching for MobileNetV3 Open
We present the next generation of MobileNets based on a combination of complementary search techniques as well as a novel architecture design. MobileNetV3 is tuned to mobile phone CPUs through a combination of hardware-aware network archit…
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Person Re-identification by Deep Learning Multi-scale Representations Open
Existing person re-identification (re-id) methods depend mostly on single-scale appearance information. This not only ignores the potentially useful explicit information of other different scales, but also loses the chance of mining the im…
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Rational Design of Capacitive Pressure Sensors Based on Pyramidal Microstructures for Specialized Monitoring of Biosignals Open
There is an increasing demand for specialized pressure sensors in various applications. Previously, capacitive pressure sensors have been shown to have wide versatility in use, with a high degree of potential tuning possible through manipu…
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FSSD: Feature Fusion Single Shot Multibox Detector Open
SSD (Single Shot Multibox Detector) is one of the best object detection algorithms with both high accuracy and fast speed. However, SSD's feature pyramid detection method makes it hard to fuse the features from different scales. In this pa…
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Visual Transformers: Token-based Image Representation and Processing for Computer Vision Open
Computer vision has achieved remarkable success by (a) representing images as uniformly-arranged pixel arrays and (b) convolving highly-localized features. However, convolutions treat all image pixels equally regardless of importance; expl…
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NAS-FPN: Learning Scalable Feature Pyramid Architecture for Object Detection Open
Current state-of-the-art convolutional architectures for object detection are manually designed. Here we aim to learn a better architecture of feature pyramid network for object detection. We adopt Neural Architecture Search and discover a…
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Path Aggregation Network for Instance Segmentation Open
The way that information propagates in neural networks is of great importance. In this paper, we propose Path Aggregation Network (PANet) aiming at boosting information flow in proposal-based instance segmentation framework. Specifically, …
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Pyramid Graph Networks With Connection Attentions for Region-Based One-Shot Semantic Segmentation Open
One-shot image segmentation aims to undertake the segmentation task of a novel class with only one training image available. The difficulty lies in that image segmentation has structured data representations, which yields a many-to-many me…
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Pre-Trained AlexNet Architecture with Pyramid Pooling and Supervision for High Spatial Resolution Remote Sensing Image Scene Classification Open
The rapid development of high spatial resolution (HSR) remote sensing imagery techniques not only provide a considerable amount of datasets for scene classification tasks but also request an appropriate scene classification choice when fac…
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Sub-Image Anomaly Detection with Deep Pyramid Correspondences Open
Nearest neighbor (kNN) methods utilizing deep pre-trained features exhibit very strong anomaly detection performance when applied to entire images. A limitation of kNN methods is the lack of segmentation map describing where the anomaly li…
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Pyramid Scene Parsing Network Open
Scene parsing is challenging for unrestricted open vocabulary and diverse scenes. In this paper, we exploit the capability of global context information by different-region-based context aggregation through our pyramid pooling module toget…
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Automatic Ship Detection Based on RetinaNet Using Multi-Resolution Gaofen-3 Imagery Open
Independent of daylight and weather conditions, synthetic aperture radar (SAR) imagery is widely applied to detect ships in marine surveillance. The shapes of ships are multi-scale in SAR imagery due to multi-resolution imaging modes and t…
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Skeleton-Based Dynamic Hand Gesture Recognition Open
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Detection of PCB Surface Defects With Improved Faster-RCNN and Feature Pyramid Network Open
Defect detection is an essential requirement for quality control in the production of printed circuit boards (PCBs) manufacturing. The traditional defect detection methods have various drawbacks, such as strongly depending on a carefully d…
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Remote Sensing Scene Classification by Unsupervised Representation Learning Open
With the rapid development of the satellite sensor technology, high spatial resolution remote sensing (HSR) data have attracted extensive attention in military and civilian applications. In order to make full use of these data, remote sens…
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Fuzzy System Based Medical Image Processing for Brain Disease Prediction Open
The present work aims to explore the performance of fuzzy system-based medical image processing for predicting the brain disease. The imaging mechanism of NMR (Nuclear Magnetic Resonance) and the complexity of human brain tissues cause the…
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Ultra‐Sensitive, Deformable, and Transparent Triboelectric Tactile Sensor Based on Micro‐Pyramid Patterned Ionic Hydrogel for Interactive Human–Machine Interfaces Open
Rapid advances in wearable electronics and mechno‐sensational human–machine interfaces impose great challenges in developing flexible and deformable tactile sensors with high efficiency, ultra‐sensitivity, environment‐tolerance, and self‐s…
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Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformers Open
Most polyp segmentation methods use convolutional neural networks (CNNs) as their backbone, leading to two key issues when exchanging information between the encoder and decoder: (1) taking into account the differences in contribution betw…
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Automatic Fabric Defect Detection with a Multi-Scale Convolutional Denoising Autoencoder Network Model Open
Fabric defect detection is a necessary and essential step of quality control in the textile manufacturing industry. Traditional fabric inspections are usually performed by manual visual methods, which are low in efficiency and poor in prec…
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Tomato detection based on modified YOLOv3 framework Open
Fruit detection forms a vital part of the robotic harvesting platform. However, uneven environment conditions, such as branch and leaf occlusion, illumination variation, clusters of tomatoes, shading, and so on, have made fruit detection v…
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Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes Open
Semantic segmentation is a key technology for autonomous vehicles to understand the surrounding scenes. The appealing performances of contemporary models usually come at the expense of heavy computations and lengthy inference time, which i…