Results 61 to 70 of about 39,255 (224)

Image Forgery Detection using ResNet50

International Journal for Research in Applied Science and Engineering Technology
Abstract: Image forgery detection is crucial in ensuring the integrity of digital media. In this study, we propose a method for detecting image tampering using Error Level Analysis (ELA) and Convolutional Neural Networks (CNNs) with a ResNet50 architecture. Leveraging the CASIA 2.0 Image Tampering Detection Dataset, which consists of authentic (Au) and
Nalluri Brahma Naidu, Thokala Kavyasree, Tadikonda Ravi Teja, Pulimela Sushma Sarayu, Sivangula Sai   +4 more
openaire   +1 more source

Deep Learning for Pretreatment Imaging‐Based Tumor and Nodal Classification in Head and Neck Squamous Cell Carcinoma: A Systematic Review and Network Meta‐Analysis

Head &Neck, EarlyView.
ABSTRACT Background Accurate pretreatment assessment of the extent of tumor invasion and status of cervical lymph node metastasis is essential for staging and treatment planning in HNSCC. Deep learning (DL) shows promise but is limited by methodological heterogeneity. Methods We conducted a systematic review and network meta‐analysis (PRISMA). Studies (
Jannik Ketschau, Alex Grabenhorst, Hannes Singer, Johannes Brandt, Helena Kram, Nils Krautkremer, Maximilian F. Miragall, Katharina Pippich, Jonathan Mohr, Klaus‐Dietrich Wolff, Lucas M. Ritschl   +10 more
wiley   +1 more source

An Intrinsically Multimodal Self‐Powered Sensor Enhanced by Microstructured Powder Layer for AI‐Enabled Tactile Perception

Interdisciplinary Materials, EarlyView.
This study presents a self‐powered, intrinsically multimodal tactile sensor capable of both static and dynamic pressure sensing. Enhanced with a microstructured polytetrafluoroethylene powder layer, it enables high‐accuracy material recognition and surface texture classification, offering AI‐compatible tactile perception for robotic systems.
Kequan Xia, Song Yang, Dong Qiang, Min Yu   +3 more
wiley   +1 more source

Transfer learning pada Network VGG16 dan ResNet50

The Indonesian Journal of Computer Science, 2023
Transfer Learning adalah prinsip yang digunakan pada neural network dengan tujuan membantu pelatihan pada data yang sedikit, mempercepat waktu dan meningkatkan performa pelatihan. Salah satu metode transfer learning adlaah fine tuning. Pada metode tersebut, melakukan pembekuan pada sejumlah layer pada model network yang dilatih sebelumnya dan melakukan
null Fauzan Muhammad, null Aniati Murni Arimurthy, null Dina Chahyati   +2 more
openaire   +1 more source

Clinical Applications of Multimodal Artificial Intelligence in Otolaryngology: A State‐of‐the‐Art Review

Otolaryngology–Head and Neck Surgery, EarlyView.
Abstract Objective Artificial intelligence (AI) has advanced to simultaneously process visual, auditory, and textual inputs, providing users with “multimodal” AI. Given the clinical integration potential of these tools, otolaryngologists must stay informed. This study reviews current literature on applications of multimodal AI in otolaryngology.
Ying Jie Li, Flora Su, Norbert Banyi, Philip Edgcumbe, Andrew Thamboo, Ameen Amanian   +5 more
wiley   +1 more source

When Fat Goes Astray: Your Liver and Pancreas Get Into Trouble

Portal Hypertension &Cirrhosis, EarlyView.
Metabolic dysfunction‐associated steatotic liver disease (MASLD) and intrapancreatic fat deposition (IPFD) are both common manifestations of ectopic fat accumulation. Although they share multiple risk factors, they also show notable differences in pathological features, standardization of diagnosis, and research maturity.
Yuying Chen, Li Ding, Shan Zhao, Weihong Wang, Jing Zhong, Qiang Yan   +5 more
wiley   +1 more source

A novel ResNet50-based attention mechanism for image classification

Journal of Applied Science and Engineering
Image classification tasks often compress the neural network model to reduce the number of parameters, which leads to a decrease in classification accuracy.
Jingsi Zhang, Xiaosheng Yu, Xiaoliang Lei, Chengdong Wu   +3 more
doaj   +1 more source

A pipeline to compile expert‐verified datasets of digitised herbarium specimens for automated plant identification to accelerate taxonomy

PLANTS, PEOPLE, PLANET, EarlyView.
Understanding and protecting plant life is essential for tackling the twin challenges of biodiversity loss and climate change. To support this, we have developed a new digital approach that helps identify plant species more quickly and accurately.
Jed Arno, Jérémie Morel, Fitiavana Rasaminirina, Juliene de Fátima Maciel‐Silva, Daniel Cahen, Damon P. Little, Daniele Silvestro, Alexandre Antonelli, Olwen Grace, Li Zhang, Isabel Larridon   +10 more
wiley   +1 more source

Improving forest age estimation to understand subtropical forest regrowth dynamics using deep learning image segmentation of time‐series historical aerial photographs

Remote Sensing in Ecology and Conservation, EarlyView.
Accurately estimating forest age is key to understanding how forests recover and evaluating restoration success. We developed a two‐step deep learning approach using historical greyscale aerial photographs to map forest age at fine spatial scales. By combining a pre‐trained model with localized fine‐tuning, our U‐Net + ResNet50 architecture achieved ...
Ying Ki Law, Yi‐Fei Gu, Shuwen Liu, Guangqin Song, Aland H. Y. Chan, Cham Man Tse, Zhonghua Liu, Martha J. Ledger, Billy C. H. Hau, Sawaid Abbas, Jin Wu   +10 more
wiley   +1 more source

Classification of Skin Cancer Images Using Convolutional Neural Network with ResNet50 Pre-trained Model

JOIV: International Journal on Informatics Visualization
The skin, an astonishingly expansive organ within the human body, plays a pivotal role in safeguarding us against the environment's harsh elements. It acts as a formidable barrier, shielding our delicate internal systems from the scorching heat of the ...
Agus Eko Minarno, Aaliyah Lusianti, Yufis Azhar, Hardianto Wibowo   +3 more
doaj   +1 more source