Results 71 to 80 of about 6,287 (187)

Deteksi Penyakit Daun Terong Menggunakan MobileNetV2

Jurnal Teknik Informatika dan Teknologi Informasi
Eggplant is a horticultural crop that is highly dependent on the health of its leaves to support growth and productivity. Leaf diseases can cause a significant reduction in crop yield if not detected early. This study aims to develop a leaf classification model for eggplant using the MobileNetV2 architecture to automatically detect leaf conditions. The
null Hardy Gustino, null Muhammad Rafi Winno Pratama, null Rafli Aldrian Kurnianto, null Anggraini Puspita Sari   +3 more
openaire   +1 more source

High-Accuracy Mapping of Coastal and Wetland Areas Using Multisensor Data Fusion and Deep Feature Learning

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Coastal and wetland regions play vital roles in ecosystem stability, economic development, and climate regulation, particularly along the rapidly changing coastline of eastern Asia.
Shumin Han, Runhong Gao, Liaqat Ali Waseem, Kasye Shitu, Nazih Y. Rebouh, Rana Muhammad Zulqarnain, Yahia Said   +6 more
doaj   +1 more source

Multisensor Data Fusion and Deep Feature-Based Classification for Mapping China’s Coastal and Wetland Areas

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Ecosystem stability, economic growth, and climate regulation are all greatly aided by coastal and wetland regions. This is particularly true in rapidly evolving regions, such as China’s extensive coastline.
Haojie Qin, Junhuan Lu, Jie Feng, Ning Zhou, Hao Liu, Libing Huang, Xun Zhou   +6 more
doaj   +1 more source

A Comparison of MobileNetV2 and VGG16 Architectures with Transfer Learning for Multi-Class Image-Based Waste Classification

Journal of Applied Informatics and Computing
Effective waste management represents a global challenge with significant environmental and public health impacts. Despite existing waste classification systems achieving high accuracy rates, a critical research gap exists in determining optimal CNN ...
Raffa Adhi Kumala, Christy Atika Sari, Eko Hari Rachmawanto   +2 more
doaj   +1 more source

A lightweight disease identification method for tea leaves based on improved MobileNetV2

Huanan Nongye Daxue xuebao
ObjectiveTo address the challenge in tea leaf disease detection, where existing deep learning models struggle to balance accuracy and efficiency, particularly unsuitable for deployment on resource-constrained embedded devices.
Shuangxi XIAO, Tongtong YAO, Can LI
doaj   +1 more source

Early Skin Cancer Detection Using the SLICE-3D Dataset: A Transfer Learning Model and DCGAN Approach to Address Data Imbalance

Cybernetics and Information Technologies
Early detection of skin cancer is crucial for improving patient outcomes, as the disease progresses rapidly when left untreated. Recent advancements in artificial intelligence have revolutionized the field of early detection, giving clinicians more ...
Mecifi Youssera Z., Merzoug Mohamed, Etchiali Abdelhak, M’hamedi Mohamed, Hadjila Fethallah, Bekkouche Amina   +5 more
doaj   +1 more source

Aircraft Image Classification on a Small-Scale Dataset using MobileNetV2 with Grad-CAM as Explainable AI

Journal of Applied Informatics and Computing
This study explores aircraft image classification using MobileNetV2 combined with Gradient-weighted Class Activation Mapping (Grad-CAM) for model interpretability.
Susi Lestari, Mohamad Alif Dzulfiqar, Ahmadi Irmansyah Lubis, Muhammad Andi Nova, Zaimah Zaimah, Mulyadi Mulyadi   +5 more
doaj   +1 more source

High Precision Deep Learning Model for Road Damage Classification using Transfer Learning

Sistemasi: Jurnal Sistem Informasi
Roads are critical infrastructure that frequently experience damage, directly impacting transportation safety and efficiency. Manual road damage inspection is time-consuming and resource-intensive, highlighting the need for automated, image-based ...
Muhammad Abdul Ghofur, Murdifin Murdifin, Awan Gumilang Hardandrito, Shofwatul 'Uyun   +3 more
doaj   +1 more source

Implementation and Comparative Analysis of CNN and Transfer Learning Models (EfficientNetB0, MobileNetV2, and ResNet50) for Rice Leaf Disease Detection Based on Digital Images

Journal of Applied Informatics and Computing
Rice leaf diseases significantly reduce agricultural productivity, making early and accurate detection essential, particularly in rice-producing regions such as Indonesia.
Tri Wahyu Utami, Mega Novita, Khoiriya Latifa   +2 more
doaj   +1 more source

Face Mask Detection using MobileNetV2

International Journal for Research in Applied Science and Engineering Technology, 2021
openaire   +1 more source