Suchergebnisse - "Martha, Sheshikala"

Investigating the recall efficiency in abstractive summarization: an experimental based comparative study.

Autoren: Surabhi Anuradha Martha Sheshikala

Quelle: Indonesian Journal of Electrical Engineering & Computer Science; Jul2025, Vol. 39 Issue 1, p446-454, 9p

Schlagwörter: LANGUAGE models, AUTOMATIC summarization, TEXT summarization, RESEARCH personnel

Retraction Note: Analysis of transcriptome of single-cell RNA sequencing data using machine learning.

Autoren: Rajesh, Mothe Martha, Sheshikala

Quelle: Soft Computing - A Fusion of Foundations, Methodologies & Applications; 2024 Suppl 1, Vol. 28, p277-277, 1p

Schlagwörter: RNA sequencing, MACHINE learning, TRANSCRIPTOMES, PUBLISHING, CONFIDENCE

Feature Dimensionality Reduction for Lung Tumor Classification Using Transformer Deep Learning and YOLO Model.

Autoren: Thaseen, Aliya Martha, Sheshikala Nandan, Durgesh

Quelle: Ingénierie des Systèmes d'Information; Jun2025, Vol. 30 Issue 6, p1425-1435, 11p

Schlagwörter: LUNG cancer, TUMOR classification, EARLY diagnosis, TRANSFORMER models, DEEP learning, MEDICAL innovations, DIMENSIONAL reduction algorithms

Detection of COVID-19 using edge devices by a light-weight convolutional neural network from chest X-ray images.

Autoren: Chauhan, Sohamkumar Edla, Damoder Reddy Boddu, Vijayasree et al.

Quelle: BMC Medical Imaging; 1/2/2024, Vol. 24 Issue 1, p1-15, 15p

Schlagwörter: CONVOLUTIONAL neural networks, X-ray imaging, COMPUTER vision, DEEP learning, COVID-19

Analysis of transcriptome of single-cell RNA sequencing data using machine learning.

Autoren: Rajesh, Mothe Martha, Sheshikala

Quelle: Soft Computing - A Fusion of Foundations, Methodologies & Applications; Jul2023, Vol. 27 Issue 13, p9131-9141, 11p

Schlagwörter: RNA sequencing, MACHINE learning, COMPUTATIONAL biology, RNA, TRANSCRIPTOMES, CELL populations

DeepSplice: a deep learning approach for accurate prediction of alternative splicing events in the human genome.

Autoren: Abrar, Mohammad Hussain, Didar Khan, Izaz Ahmad et al.

Quelle: Frontiers in Genetics; 2024, p01-12, 12p

Schlagwörter: ALTERNATIVE RNA splicing, HUMAN genome, DEEP learning, MACHINE learning, HUMAN physiology, INFORMATION processing

ICT Systems and Sustainability

Autoren: Milan Tuba Shyam Akashe Amit Joshi

Resource Type: eBook.

Categories: COMPUTERS / Artificial Intelligence / General

Recent Trends in Image Processing and Pattern Recognition

Autoren: KC Santosh Aaisha Makkar Myra Conway et al.

Resource Type: eBook.

Schlagworte: Image processing—Digital techniques, Computer vision, Artificial intelligence, Computer systems, Social sciences—Data processing, Application software

Categories: COMPUTERS / Artificial Intelligence / Computer Vision & Pattern Recognition, COMPUTERS / Artificial Intelligence / General, COMPUTERS / Business & Productivity Software / General, COMPUTERS / Computer Architecture, COMPUTERS / Image Processing, COMPUTERS / Hardware / General