Deep learning for Covid-19 forecasting: State-of-the-art review.

F Kamalov, K Rajab, AK Cherukuri, A Elnagar… - Neurocomputing, 2022 - Elsevier
The Covid-19 pandemic has galvanized scientists to apply machine learning methods to
help combat the crisis. Despite the significant amount of research there exists no …

Advances in online handwritten recognition in the last decades

T Ghosh, S Sen, SM Obaidullah, KC Santosh… - Computer Science …, 2022 - Elsevier
The easy availability and rapid use of online devices like Take note, PDA, smartphones, etc.
at an affordable price increase the demand for online handwriting recognition. In this …

An empirical survey of data augmentation for time series classification with neural networks

BK Iwana, S Uchida - Plos one, 2021 - journals.plos.org
In recent times, deep artificial neural networks have achieved many successes in pattern
recognition. Part of this success can be attributed to the reliance on big data to increase …

Intrinsic sense of touch for intuitive physical human-robot interaction

M Iskandar, A Albu-Schäffer, A Dietrich - Science Robotics, 2024 - science.org
The sense of touch is a property that allows humans to interact delicately with their physical
environment. This article reports on a technological advancement in intuitive human-robot …

A scalable handwritten text recognition system

RR Ingle, Y Fujii, T Deselaers… - … on document analysis …, 2019 - ieeexplore.ieee.org
Many studies on (Offline) Handwritten Text Recognition (HTR) systems have focused on
building state-of-the-art models for line recognition on small corpora. However, adding HTR …

An automatic system to monitor the physical distance and face mask wearing of construction workers in COVID-19 pandemic

M Razavi, H Alikhani, V Janfaza, B Sadeghi… - SN computer …, 2022 - Springer
The COVID-19 pandemic has caused many shutdowns in different industries around the
world. Sectors such as infrastructure construction and maintenance projects have not been …

Vectorization and rasterization: Self-supervised learning for sketch and handwriting

AK Bhunia, PN Chowdhury, Y Yang… - Proceedings of the …, 2021 - openaccess.thecvf.com
Self-supervised learning has gained prominence due to its efficacy at learning powerful
representations from unlabelled data that achieve excellent performance on many …

Modelling and prediction of GNSS time series using GBDT, LSTM and SVM machine learning approaches

W Gao, Z Li, Q Chen, W Jiang, Y Feng - Journal of Geodesy, 2022 - Springer
Global navigation satellite system (GNSS) site coordinate time series provides essential
data for geodynamic and geophysical studies, realisation of a regional or global geodetic …

IDS-attention: an efficient algorithm for intrusion detection systems using attention mechanism

FE Laghrissi, S Douzi, K Douzi, B Hssina - Journal of Big Data, 2021 - Springer
Network attacks are illegal activities on digital resources within an organizational network
with the express intention of compromising systems. A cyber attack can be directed by …

DT2F-TLNet: A novel text-independent writer identification and verification model using a combination of deep type-2 fuzzy architecture and Transfer Learning …

J Yang, M Shokouhifar, L Yee, AA Khan… - Expert Systems with …, 2024 - Elsevier
Identifying and verifying the identity of people based on scanned images of handwritten
documents is an applicable biometric modality with applications in forensic and historic …