Results 101 to 110 of about 28,970 (210)

RNA Modifications: Current Understandings and Future Perspectives

MedComm, Volume 7, Issue 5, May 2026.
Types of RNA modification. We have summarized the currently common types of RNA modifications, including ac4C, m6A, m1A, m5C, m3C, m7G, and ψ, and visually characterized their features through structural formulas. The characteristic structures are marked with a background color different from the background color.
Shiyu Xiao, Tingwen Xiang, Chuan Yang, Xiaohua Wang, Gang Huang, Fei Luo, Zhao Xie, Yueqi Chen   +7 more
wiley   +1 more source

Hybrid deep learning models for automatic segmentation and classification of breast lesions in ultrasound images

The Egyptian Journal of Radiology and Nuclear Medicine
Background and purpose Breast cancer requires early detection for effective treatment. Although ultrasound offers high sensitivity and is less invasive, it still faces challenges such as speckle noise and complex tissue textures.
Ali Rahimnezhad, Seyed Masoud Rezaeijo, Mohammad Parsa Bayat, Sahel Heydarheydari   +3 more
doaj   +1 more source

Efficient Classification of Pomegranate Diseases Using Deep Learning Models and Interactive Visualization [PDF]

EPJ Web of Conferences
This work tackles the growing hazard of pomegranate infections by utilizing deep learning for early detection and control. We created a strong classification system by implementing models with TensorFlow, Keras, and NumPy, as well as a user-friendly ...
Mishra Gaurav, Nagaonkar Jagruti, Parmar Harsh, Joshi Gaurav   +3 more
doaj   +1 more source

Interpretable CRAM‑Enhanced Lightweight Dual‑Branch CNN for Real‑Time Breast Cancer Histopathology in Internet‑of‑Medical‑Things Environments

Small, Volume 22, Issue 26, 8 May 2026.
This study presents an interpretable, lightweight hybrid deep learning model for real‐time analysis of breast cancer histopathology in IoMT‐enabled diagnostic systems. By integrating MobileNetV2 and EfficientNet‐B0 with a novel contextual recurrent attention module (CRAM), the framework achieves near‐perfect accuracy while providing transparent Grad ...
Roseline Oluwaseun Ogundokun, Rotimi‐Williams Bello, Pius Adewale Owolawi, Rytis Maskeliūnas, Abdulsatar Abduljabbar Sultan   +4 more
wiley   +1 more source

AI‐Enabled Imaging for Pathogen Detection Under Stress Conditions: A Systematic Review

Comprehensive Reviews in Food Science and Food Safety, Volume 25, Issue 3, May 2026.
ABSTRACT Advances in pathogen detection that incorporate artificial intelligence (AI) may capture microbial signals under challenging environmental conditions that traditional methods miss. This systematic review evaluates the application, performance, and methodological characteristics of AI‐enabled imaging for pathogen detection, including its impact
MeiLi Papa, Gillian Kuehnle, Yoo Jung (Erika) Oh, Jiyoon Yi   +3 more
wiley   +1 more source

Precision meets generalization: Enhancing brain tumor classification via pretrained DenseNet with global average pooling and hyperparameter tuning.

PLoS ONE
Brain tumors pose significant global health concerns due to their high mortality rates and limited treatment options. These tumors, arising from abnormal cell growth within the brain, exhibits various sizes and shapes, making their manual detection from ...
Najam Aziz, Nasru Minallah, Jaroslav Frnda, Madiha Sher, Muhammad Zeeshan, Amara Haroon Durrani   +5 more
doaj   +1 more source

Optimized DenseNet Architectures for Precise Classification of Edible and Poisonous Mushrooms

International Journal of Computational Intelligence Systems
Background The subtle differences between edible and toxic mushroom species make classification difficult. Traditional methods often result in errors which led to misclassifications and conventional machine learning models often struggle in feature ...
Jay Prakash Singh, Debolina Ghosh, Jagannath Singh, Anurag Bhattacharjee, Mahendra Kumar Gourisaria   +4 more
doaj   +1 more source

An Improved Neural Network Model Based on DenseNet for Fabric Texture Recognition

Sensors
In modern knitted garment production, accurate identification of fabric texture is crucial for enabling automation and ensuring consistent quality control.
Li Tan, Qiang Fu, Jing Li
doaj   +1 more source

Research on Pneumothorax Classification Model of DenseNet Based on Multilayer Network Optimization

Journal of Mathematics
This article establishes the DenseNet based on multilayer network optimization (DenseNet-MNO) using a binary dataset of pneumothorax. This method optimizes multiple network layers and ensures the convergence of the neural network by reducing the learning
Hongliang Huang, Qike Wang, Lidong Wang
doaj   +1 more source

DenseNet Models for Tiny ImageNet Classification

, 2019
In this paper, we present two image classification models on the Tiny ImageNet dataset. We built two very different networks from scratch based on the idea of Densely Connected Convolution Networks. The architecture of the networks is designed based on the image resolution of this specific dataset and by calculating the Receptive Field of the ...
Abai, Zoheb, Rajmalwar, Nishad
openaire   +2 more sources