Two decades of bengali handwritten digit recognition: A survey

ABMA Rahman, MB Hasan, S Ahmed, T Ahmed… - IEEE …, 2022 - ieeexplore.ieee.org
Handwritten Digit Recognition (HDR) is one of the most challenging tasks in the domain of
Optical Character Recognition (OCR). Irrespective of language, there are some inherent …

Artificial intelligence based handwriting digit recognition (hdr)-a technical review

Y Yogesh, GSP Ghantasala… - … Conference on Device …, 2023 - ieeexplore.ieee.org
The ability of a computer to recognise and interpret handwritten input is referred to as"
handwritten text recognition," proving an intangible ability for artificial intelligence (AI). The …

[HTML][HTML] Computer vision-based six layered convneural network to recognize sign language for both numeral and alphabet signs

MA Rahaman, KU Oyshe, PK Chowdhury… - Biomimetic Intelligence …, 2024 - Elsevier
People who have trouble communicating verbally are often dependent on sign language,
which can be difficult for most people to understand, making interaction with them a difficult …

An efficient transfer learning-based approach for apple leaf disease classification

MH Ashmafee, T Ahmed, S Ahmed… - 2023 International …, 2023 - ieeexplore.ieee.org
Correct identification and categorization of plant diseases are crucial for ensuring the safety
of the global food supply and the overall financial success of stakeholders. In this regard, a …

[PDF][PDF] QMX-BdSL49: An Efficient Recognition Approach for Bengali Sign Language with Quantize Modified Xception

N Begum, SS Khan, R Rahman, A Haque… - … Journal of Advanced …, 2023 - researchgate.net
Sign language is developed to bridge the communication gap between individuals with and
without hearing impairment or speech difficulties. Individuals with hearing and speech …

Improved Speech Emotion Recognition in Bengali Language using Deep Learning

S Aziz, NH Arif, S Ahbab, S Ahmed… - … on Computer and …, 2023 - ieeexplore.ieee.org
Speech Emotion Recognition (SER) is an evolving field at the intersection of artificial
intelligence and signal processing. Despite there being notable advancements leveraging …

Performance Analysis of Machine Learning Algorithms for Autism Spectrum Disorder Level Detection using Behavioural Symptoms

ST Tasmi, S Ahmed… - 2023 26th International …, 2023 - ieeexplore.ieee.org
Autism Spectrum Disorder (ASD) is a neurological disorder that can impact personal and
social life and create difficulties in leading a normal life. As a widely discussed global issue …

Structure-enhanced translation from pet to ct modality with paired gans

T Ahmed, A Munir, S Ahmed, MB Hasan… - Proceedings of the …, 2023 - dl.acm.org
Computed Tomography (CT) images play a crucial role in medical diagnosis and treatment
planning. However, acquiring CT images can be difficult in certain scenarios, such as …

Sign Language Recognition Using Machine Learning

M Soundarya, M Yazhini, NT Sree… - … on Advances in …, 2024 - ieeexplore.ieee.org
The community of the deaf and hearing-impaired uses sign language as the primary but not
exclusively dominant mode of communication. A strong system that can translate spoken …

An Evaluation of BdSL 49 Dataset Using Transfer Learning Techniques: A Review

SS Khan, A Haque, N Khatun, N Begum… - Proceedings of the …, 2023 - Springer
Sign language is used to communicate using hand movements rather than words or written
language. Typically, this approach is useful for the deaf or mute people since they cannot …