Results 61 to 70 of about 5,255 (193)

Unleashing Modified Deep Learning Models in Efficient COVID19 Detection

, 2023
The COVID19 pandemic, a unique and devastating respiratory disease outbreak, has affected global populations as the disease spreads rapidly. Recent Deep Learning breakthroughs may improve COVID19 prediction and forecasting as a tool of precise and fast ...
Islam, Md Aminul, Raihan, M, Rony, Mohammad Abu Tareq, Shuvo, Shabbir Ahmed, Sufian, Md Abu   +4 more
core  

Comparative Study of Deep Learning Models to Classify of Multi-Class Skin Cancer on Imbalanced Data

Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI)
Skin cancer diagnosis faces challenges in efficiency and accuracy. This research addresses the need for improved non-invasive diagnostic tools by leveraging deep learning for multi-class skin cancer classification from dermoscopic images. A key focus is
Widhia KZ Oktoeberza, Muhammad Farchan Al Rahman, Azvadennys Vasiguhamiaz, Widya Nurul Huda, Afdhal Kurniawan Mainil, Julia Purnama Sari   +5 more
doaj   +1 more source

Penerapan Pre-Trained Networks untuk Deteksi Jenis Tanaman Herbal Berdasarkan Citra Daun [PDF]

Indonesia memiliki jenis tanaman herbal yang cukup banyak. Tanamanan herbal memiliki kebermanfaatan untuk kesehatan yang digunakan masyarakat secara luas sebagai pengobatan tradional.
Akmal, Refido Arjunal, Hartati, Sri, Kurniasih, Aliyah   +2 more
core   +2 more sources

MMLTC: A Novel Tolerance‐Based Clustering Framework for Multimodal Sentiment and Harmful Meme Classification in Multilingual Settings

Computational Intelligence, Volume 42, Issue 2, April 2026.
ABSTRACT This work introduces a novel Tolerance‐Based Clustering Framework (MMLTC) framework for affective analytics of multimodal/multilingual content in social media. A key feature of the MMLTC framework is its ability to overcome limitations of prior tolerance‐based classifiers through the construction of label specific pure tolerance classes ...
Jaher Hassan Chowdhury, Sheela Ramanna
wiley   +1 more source

A System to Classify Chronic Obstructive Pulmonary Disease using Pre-trained-Densenet201 with TSA

Measurement: Sensors
COPD (Chronic obstructive pulmonary disease), ranking as the 3rd most common cause of death worldwide, frequently goes undiagnosed. Yet, the detection of COPD in its early stages is challenging due to the limited presence or mild nature of initial ...
F. Fanax Femy, G. Nallasivan, K. Basarikodi, C. Natarajan, A. Bhuvanesh, T. Swapna   +5 more
doaj   +1 more source

CNN‐Based Accent Similarity Detection Using Masked Spectrogram Reconstruction

Engineering Reports, Volume 8, Issue 3, March 2026.
Convolutional Neural Network Masked Spectrogram Reconstruction model to enhance accent recognition and similarity assessment in automatic speech recognition. Addressing challenges in recognizing non‐native English accents, the method utilizes randomly masked spectrogram inputs to extract accent‐specific features.
Amina Salifu, Henry Nunoo‐Mensah, Eric Tutu Tchao, Albert Dede, Francisca Adoma Acheampong, Matthew Cobbinah, Julius Adinkrah, Andrew Selasi Agbemenu, Jerry John Kponyo   +8 more
wiley   +1 more source

Improving Detection and Classification Of Brain Tumors Using DenseNet201

Journal of Science and Technology
Brain tumors are among the leading causes of death worldwide. A brain tumor may originate in the brain or develop elsewhere in the body and metastasize to the brain, leading to secondary brain tumors. Thus, brain tumors can take many different forms.
Nashwan Amin Al-khulaidi, Mohammed Hashem Almourish, Emad Mahmood Ahmed Taleb, Rasheed Abdullah Ali Farhan, Mohammed Nabil Mohammed Latf, Omar Mukhtar Ahmed Abdullah   +5 more
openaire   +1 more source

Loss‐Based Ensemble Generative Adversarial Network Model for Enhancing the Sperm Morphology Classification

Advanced Intelligent Systems, Volume 8, Issue 2, February 2026.
A loss‐based ensemble generative adversarial network (GAN) framework is proposed to address mode collapse in sperm morphology classification. By integrating spatial augmentation and multiple GAN models, the study enhances synthetic data quality. The Shifted Window Transformer achieves 95.37% accuracy on the HuSHeM dataset, outperforming previous ...
Berke Cansiz, Hamza Osman Ilhan, Gorkem Serbes   +2 more
wiley   +1 more source

Screening of oral potentially malignant disorders and oral cancer using deep learning models

Scientific Reports
Oral cancer though preventable, shows high mortality and affect the overall quality of life when detected in late stages. Screening techniques that enable early diagnosis are the need of the hour. The present work aims to evaluate the effectiveness of AI
Karishma Madhusudan Desai, Pragya Singh, Mahima Smriti, Vivek Talwar, Manav Chaudhary, George Paul, Subhas Chandra Kolli, Parisa Sai Raghava, Golla Vamshi Krishna, C. V. Jawahar, P. K. Vinod, Varma Konala, Ramanathan Sethuraman   +12 more
doaj   +1 more source

Robust Citrus Disease Diagnosis: A Hybrid CNN Framework for Multi‐Task Classification, Severity Estimation, and Cross‐Species Adaptation

Engineering Reports, Volume 8, Issue 2, February 2026.
We propose a hybrid CNN–ML approach to accurately classify diseases in lemon and orange leaves and assess their severity. Our model achieves high accuracy and demonstrates generalizability, showing promise for automated disease detection and management in citrus crops.
Sayma Akter Rupa, Khandoker Nosiba Arifin, Md Musfique Anwar   +2 more
wiley   +1 more source