[HTML][HTML] Deep learning in food category recognition

Y Zhang, L Deng, H Zhu, W Wang, Z Ren, Q Zhou… - Information …, 2023 - Elsevier
Integrating artificial intelligence with food category recognition has been a field of interest for
research for the past few decades. It is potentially one of the next steps in revolutionizing …

[HTML][HTML] Breast cancer diagnosis: A systematic review

X Wen, X Guo, S Wang, Z Lu, Y Zhang - Biocybernetics and Biomedical …, 2024 - Elsevier
The second-leading cause of death for women is breast cancer. Consequently, a precise
early diagnosis is essential. With the rapid development of artificial intelligence, computer …

Hyperspectral pathology image classification using dimension-driven multi-path attention residual network

X Zhang, W Li, C Gao, Y Yang, K Chang - Expert Systems with Applications, 2023 - Elsevier
Hyperspectral imaging technology (HSI) can capture pathological tissue's spatial and
spectral information simultaneously, with wide coverage and high accuracy characteristics …

Thermal image-based hand gesture recognition for worker-robot collaboration in the construction industry: A feasible study

H Wu, H Li, HL Chi, Z Peng, S Chang, Y Wu - Advanced Engineering …, 2023 - Elsevier
Worker-robot collaboration (WRC) is a promising solution for complex construction tasks,
which can integrate the robots' advantages in strength and accuracy with human ability in …

Automated door placement in architectural plans through combined deep-learning networks of ResNet-50 and Pix2Pix-GAN

S Kim, J Lee, K Jeong, J Lee, T Hong, J An - Expert Systems with …, 2024 - Elsevier
Previous studies on automating building design with deep learning primarily focused on
planning room layouts, limiting the design of architectural elements such as doors and …

Improving breast cancer detection and diagnosis through semantic segmentation using the Unet3+ deep learning framework

T Alam, WC Shia, FR Hsu, T Hassan - Biomedicines, 2023 - mdpi.com
We present an analysis and evaluation of breast cancer detection and diagnosis using
segmentation models. We used an advanced semantic segmentation method and a deep …

GAN-based vision Transformer for high-quality thermal image enhancement

MA Marnissi, A Fathallah - … of the IEEE/CVF Conference on …, 2023 - openaccess.thecvf.com
Abstract Generative Adversarial Networks (GANs) have shown an outstanding ability to
generate high-quality images with visual realism and similarity to real images. This paper …

Cancer detection in breast cells using a hybrid method based on deep complex neural network and data mining

L Yang, S Peng, RO Yahya, L Qian - Journal of Cancer Research and …, 2023 - Springer
Introduction Diagnosis of cancer in breast cells is an important and vital issue in the field of
medicine. In this context, the use of advanced methods such as deep complex neural …

Deep Learning in Breast Cancer Imaging: State of the Art and Recent Advancements in Early 2024

A Carriero, L Groenhoff, E Vologina, P Basile, M Albera - Diagnostics, 2024 - mdpi.com
The rapid advancement of artificial intelligence (AI) has significantly impacted various
aspects of healthcare, particularly in the medical imaging field. This review focuses on …

Breast cancer diagnosis using optimized deep convolutional neural network based on transfer learning technique and improved Coati optimization algorithm

MM Emam, EH Houssein, NA Samee… - Expert Systems with …, 2024 - Elsevier
Breast cancer is a significant health concern due to its aggressive nature and high mortality
rates. Early detection is crucial to improving patient outcomes. Thermography, a non …