A synchronous detection-segmentation method for oversized gangue on a coal preparation plant based on multi-task learning
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
A synchronous detection-segmentation method for oversized gangue on a coal preparation plant based on multi-task learning
Authors
Keywords
-
Journal
MINERALS ENGINEERING
Volume 187, Issue -, Pages 107806
Publisher
Elsevier BV
Online
2022-08-28
DOI
10.1016/j.mineng.2022.107806
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Coal gangue image segmentation method based on edge detection theory of star algorithm
- (2022) Xinquan Wang et al. International Journal of Coal Preparation and Utilization
- Gradient- enhanced waterpixels clustering for coal gangue image segmentation
- (2022) Chengcai Fu et al. International Journal of Coal Preparation and Utilization
- Multi-scale coal and gangue dual-energy X-ray image concave point detection and segmentation algorithm
- (2022) Lei He et al. MEASUREMENT
- Fast identification model for coal and gangue based on the improved tiny YOLO v3
- (2022) Hongguang Pan et al. Journal of Real-Time Image Processing
- A Review of Deep-Learning-Based Medical Image Segmentation Methods
- (2021) Xiangbin Liu et al. Sustainability
- Coal and Gangue Separating Robot System Based on Computer Vision
- (2021) Zhiyuan Sun et al. SENSORS
- Efficient image segmentation based on deep learning for mineral image classification
- (2021) Yang Liu et al. ADVANCED POWDER TECHNOLOGY
- Fine-grained object detection method using attention mechanism and its application in coal-gangue detection
- (2021) Ziqi Lv et al. APPLIED SOFT COMPUTING
- Experimental study on separation of lumpish coal and gangue using X-ray
- (2021) Yong Zhang et al. Energy Sources Part A-Recovery Utilization and Environmental Effects
- Computer vision detection of foreign objects in coal processing using attention CNN
- (2021) Kanghui Zhang et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- Rapid ash content determination method for coal particles through images captured under multiple ring light sources with various incident angles
- (2021) Feiyan Bai et al. FUEL
- Deep learning semantic segmentation of opaque and non-opaque minerals from epoxy resin in reflected light microscopy images
- (2021) Michel Pedro Filippo et al. MINERALS ENGINEERING
- Application of concave point matching algorithm in segmenting overlapping coal particles in X-ray images
- (2021) Aiyun Sun et al. MINERALS ENGINEERING
- Rethinking semantic-visual alignment in zero-shot object detection via a softplus margin focal loss
- (2021) Qianzhong Li et al. NEUROCOMPUTING
- Impact-slip experiments and systematic study of coal gangue “category” recognition technology part II: Improving effect of the proposed parallel voting system method on coal gangue “category” recognition accuracy based on impact-slip experiments
- (2021) Yang Yang et al. POWDER TECHNOLOGY
- Identification of maceral groups in Chinese bituminous coals based on semantic segmentation models
- (2021) Yue Wang et al. FUEL
- Impact-slip experiments and systematic study of coal gangue “category” recognition technology Part I: Impact-slip experiments between coal gangue mixture and top coal caving hydraulic support and the study of coal gangue “category” recognition technology
- (2021) Yang Yang et al. POWDER TECHNOLOGY
- Application of Deep Learning in Petrographic Coal Images Segmentation
- (2021) Sebastian Iwaszenko et al. Minerals
- Autonomous Multiple Tramp Materials Detection in Raw Coal Using Single-Shot Feature Fusion Detector
- (2021) Dongjun Li et al. Applied Sciences-Basel
- Video detection of foreign objects on the surface of belt conveyor underground coal mine based on improved SSD
- (2020) Yuanbin Wang et al. Journal of Ambient Intelligence and Humanized Computing
- Cascade network for detection of coal and gangue in the production context
- (2020) Ziqi Lv et al. POWDER TECHNOLOGY
- Image segmentation method for coal particle size distribution analysis
- (2020) Feiyan Bai et al. Particuology
- Deep High-Resolution Representation Learning for Visual Recognition
- (2020) Jingdong Wang et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Performance analysis of optical and X-Ray transmitter sensors for limestone classification in the South of Brazil
- (2019) Régis Sebben Paranhos et al. Journal of Materials Research and Technology-JMR&T
- A survey on deep learning techniques for image and video semantic segmentation
- (2018) Alberto Garcia-Garcia et al. APPLIED SOFT COMPUTING
- Research on methods to differentiate coal and gangue using image processing and a support vector machine
- (2018) Weidong Wang et al. International Journal of Coal Preparation and Utilization
- An overview of multi-task learning
- (2017) Yu Zhang et al. National Science Review
Find the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
SearchAdd your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload Now