Results 21 to 30 of about 554,243 (265)

A Contrastive Learning Network for Performance Metric and Assessment of Physical Rehabilitation Exercises

IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023
Human activity analysis in the legal monitoring environment plays an important role in the physical rehabilitation field, as it helps patients with physical injuries improve their postoperative conditions and reduce their medical costs. Recently, several
Long Yao, Qing Lei, Hongbo Zhang, Jixiang Du, Shangce Gao   +4 more
doaj   +1 more source

Self-Attention in Reconstruction Bias U-Net for Semantic Segmentation of Building Rooftops in Optical Remote Sensing Images

Remote Sensing, 2021
Deep learning models have brought great breakthroughs in building extraction from high-resolution optical remote-sensing images. Among recent research, the self-attention module has called up a storm in many fields, including building extraction. However,
Ziyi Chen, Dilong Li, Wentao Fan, Haiyan Guan, Cheng Wang, Jonathan Li   +5 more
doaj   +1 more source

Building and road detection from remote sensing images based on weights adaptive multi-teacher collaborative distillation using a fused knowledge

International Journal of Applied Earth Observations and Geoinformation, 2023
Knowledge distillation is one effective approach to compress deep learning models. However, the current distillation methods are relatively monotonous. There are still rare studies about the combination of distillation strategies using multiple types of ...
Ziyi Chen, Liai Deng, Jing Gou, Cheng Wang, Jonathan Li, Dilong Li   +5 more
doaj   +1 more source

Direction Estimation for Pedestrian Monitoring System in Smart Cities: An HMM Based Approach

IEEE Access, 2016
The paper proposes a novel approach for direction estimation of a moving pedestrian as perceived in a 2-D coordinate of field camera. The proposed direction estimation method is intended for pedestrian monitoring in traffic control systems.
Rahul Raman, Pankaj Kumar Sa, Banshidhar Majhi, Sambit Bakshi   +3 more
doaj   +1 more source

Lattice and Imbalance Informed Multi-Label Learning

IEEE Access, 2020
In a multi-label dataset, an instance is given a single representation across all possible labels. Despite the mutual sharing of instances among the labels, the membership of the instances vary from label to label.
Payel Sadhukhan, Sarbani Palit
doaj   +1 more source

Road extraction in remote sensing data: A survey

International Journal of Applied Earth Observations and Geoinformation, 2022
Automated extraction of roads from remotely sensed data come forth various usages ranging from digital twins for smart cities, intelligent transportation, urban planning, autonomous driving, to emergency management. Many studies have focused on promoting
Ziyi Chen, Liai Deng, Yuhua Luo, Dilong Li, José Marcato Junior, Wesley Nunes Gonçalves, Abdul Awal Md Nurunnabi, Jonathan Li, Cheng Wang, Deren Li   +9 more
doaj   +1 more source

Depth‐based end‐to‐end deep network for human action recognition

IET Computer Vision, 2019
Recognition of human actions from videos can be improved if depth information is available. Depth information certainly helps in segregating foreground motion from the background.
Sachin Chaudhary, Subrahmanyam Murala
doaj   +1 more source

Explainable Deep Learning System for Advanced Silicon and Silicon Carbide Electrical Wafer Defect Map Assessment

IEEE Access, 2022
The recent increasing demand of Silicon-on-Chip devices has triggered a significant impact on the industrial processes of leading semiconductor companies.
Riccardo Emanuele Sarpietro, Carmelo Pino, Salvatore Coffa, Angelo Messina, Simone Palazzo, Sebastiano Battiato, Concetto Spampinato, Francesco Rundo   +7 more
doaj   +1 more source

Combining Morphological and Histogram based Text Line Segmentation in the OCR Context [PDF]

Journal of Data Mining and Digital Humanities, 2021
Text line segmentation is one of the pre-stages of modern optical character recognition systems. The algorithmic approach proposed by this paper has been designed for this exact purpose.
Pit Schneider
doaj   +1 more source

A feasibility cachaca type recognition using computer vision and pattern recognition [PDF]

, 2016
Brazilian rum (also known as cachaça) is the third most commonly consumed distilled alcoholic drink in the world, with approximately 2.5 billion liters produced each year.
Caliari, Márcio, Cardoso, Karla Cristina Rodrigues, Coelho, C.J., Costa, Ronaldo Martins da, Delbem, A.C.B., Federson, F.M., Laureano, G.T., Lima, T.W., Ribeiro, Tânia Isabel Monteiro, Rodrigues, Bruno Urbano, Salvini, R.L., Silva, Flávio Alves da, Soares, Anderson da Silva, Van Baalen, J.   +13 more
core   +1 more source