Remote Sensing Image Interpretation: Deep Belief Networks for Multi-Object Analysis

MW Ahmed, A Alshahrani, A Almjally… - Ieee …, 2024 - ieeexplore.ieee.org
Object Classification in Remote Sensing Imagery holds paramount importance for extracting
meaningful insights from complex aerial scenes. Conventional methods encounter …

Optimizing energy-efficient cluster head selection in wireless sensor networks using a binarized spiking neural network and honey badger algorithm

AJ Wilson, WS Kiran, AS Radhamani… - Knowledge-Based …, 2024 - Elsevier
Abstract Wireless Sensor Networks (WSNs) play a vitalparton some applications, like
environmental monitoring, healthcare, industrial automation. Optimizing the performance of …

[HTML][HTML] Research on Target Image Classification in Low-Light Night Vision

Y Li, Y Luo, Y Zheng, G Liu, J Gong - Entropy, 2024 - mdpi.com
In extremely dark conditions, low-light imaging may offer spectators a rich visual experience,
which is important for both military and civic applications. However, the images taken in ultra …

Vision-based identification of tire inflation pressure using Tire-YOLO and deflection

J Zhang, J Peng, X Kong, L Deng, EJ OBrien - Measurement, 2025 - Elsevier
Tire inflation pressure has a significant impact on vehicle performance and safety. Existing
tire pressure identification methods rely on sensors, which have limitations such as high …

A Deep Learning with Metaheuristic Optimization-Driven Breast Cancer Segmentation and Classification Model using Mammogram Imaging

M Sreevani, R Latha - Engineering, Technology & Applied Science …, 2025 - etasr.com
Cancer is the second leading cause of death globally, with Breast Cancer (BC) accounting
for 20% of the new diagnoses, making it a major cause of morbidity and mortality …

Diagnosis of digital mammograms using computer-assisted system: A Review

A Mishra, S Rup, F Mohanty - 2024 International Conference on …, 2024 - ieeexplore.ieee.org
In recent decades, breast cancer has been consid ered the leading cause of death in
Women. Therefore, raising awareness about early detection and diagnosis of breast cancer …

A Comparative Study of Image Segmentation Techniques in Mammograms (Otsu Thresholding, FCM, and U-Net)

HR Fajrin, Y Kim, SD Min - 2024 International Conference on …, 2024 - ieeexplore.ieee.org
This study aims to employ three image segmentation techniques—Thresholding (Otsu's
method), Fuzzy C-Means (FCM) clustering, and the U-Net deep learning model-on …

Bacterial Foraging Optimization Algorithm with Deep Learning Method to EnhanceBreast Cancer Detection using Digital Mammography

D Banumathy, D Karthikeyan, G Mohanraj… - 2024 - researchsquare.com
This study focuses on improving the detection of breast cancer at an early stage. The
standard approach for diagnosing breast cancer is mammography, but it is pretty tedious as …