[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Xu et al., 2020 - Google Patents

BANet: A balanced atrous net improved from SSD for autonomous driving in smart transportation

Xu et al., 2020

Document ID
3842043477776406714
Author
Xu X
Zhao J
Li Y
Gao H
Wang X
Publication year
Publication venue
IEEE Sensors Journal

External Links

Snippet

Object detection for autonomous driving in smart transportation systems requires comprehensive consideration of accuracy, speed and sensitivity for detecting multi-objects. The one-stage algorithm, Single Shot MultiBox Detector (SSD), can basically satisfy the …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46—Extraction of features or characteristics of the image
    • G06K9/4604—Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6267—Classification techniques
    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/68—Methods or arrangements for recognition using electronic means using sequential comparisons of the image signals with a plurality of references in which the sequence of the image signals or the references is relevant, e.g. addressable memory
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30781—Information retrieval; Database structures therefor; File system structures therefor of video data
    • G06F17/30784—Information retrieval; Database structures therefor; File system structures therefor of video data using features automatically derived from the video content, e.g. descriptors, fingerprints, signatures, genre
    • G06F17/30799—Information retrieval; Database structures therefor; File system structures therefor of video data using features automatically derived from the video content, e.g. descriptors, fingerprints, signatures, genre using low-level visual features of the video content
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/20—Image acquisition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10024—Color image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass

Similar Documents

Publication Publication Date Title
Xu et al. BANet: A balanced atrous net improved from SSD for autonomous driving in smart transportation
Yuan et al. Gated CNN: Integrating multi-scale feature layers for object detection
Li et al. A survey on semantic segmentation
Chen et al. Saliency detection via the improved hierarchical principal component analysis method
Xiao et al. Deep learning for occluded and multi‐scale pedestrian detection: A review
CN109543632A (en) A kind of deep layer network pedestrian detection method based on the guidance of shallow-layer Fusion Features
Liu et al. Pedestrian detection algorithm based on improved SSD
Cho et al. Semantic segmentation with low light images by modified CycleGAN-based image enhancement
CN111832453B (en) Unmanned scene real-time semantic segmentation method based on two-way deep neural network
Sun et al. IRDCLNet: Instance segmentation of ship images based on interference reduction and dynamic contour learning in foggy scenes
Liu et al. Analysis of anchor-based and anchor-free object detection methods based on deep learning
Ajagbe et al. Performance investigation of two-stage detection techniques using traffic light detection dataset
CN114708566A (en) Improved YOLOv 4-based automatic driving target detection method
Yang et al. Multiclass objects detection algorithm using DarkNet-53 and DenseNet for intelligent vehicles
Li et al. Real-time tracking algorithm for aerial vehicles using improved convolutional neural network and transfer learning
Wang et al. PPDet: A novel infrared pedestrian detection network in a per-pixel prediction fashion
Huang et al. Pedestrian detection using RetinaNet with multi-branch structure and double pooling attention mechanism
Shi et al. Adaptive threshold cascade faster RCNN for domain adaptive object detection
Cao et al. A new region proposal network for far-infrared pedestrian detection
Sun et al. Semantic-aware 3D-voxel CenterNet for point cloud object detection
Lu et al. Multimode Gesture Recognition Algorithm Based on Convolutional Long Short‐Term Memory Network
Xue et al. Multi‐scale pedestrian detection with global–local attention and multi‐scale receptive field context
Mao et al. Split-and-Shuffle Detector for Real-Time Traffic Object Detection in Aerial Image
CN117456449B (en) Efficient cross-modal crowd counting method based on specific information
Zhang et al. Bus passenger flow statistics algorithm based on deep learning