Results 111 to 120 of about 39,255 (224)

Explanation strategies in humans versus current explainable artificial intelligence: Insights from image classification

British Journal of Psychology, Volume 117, Issue 2, Page 479-502, May 2026.
Abstract Explainable AI (XAI) methods provide explanations of AI models, but our understanding of how they compare with human explanations remains limited. Here, we examined human participants' attention strategies when classifying images and when explaining how they classified the images through eye‐tracking and compared their attention strategies ...
Ruoxi Qi, Yueyuan Zheng, Yi Yang, Caleb Chen Cao, Janet H. Hsiao   +4 more
wiley   +1 more source

Enhanced Deep Learning Approaches for Diagnosing Drilling Machine Failures Using Gramian Angular Field and Markov Transition Field Encoding

Journal of Applied Science and Engineering
In the era of Industry 4.0, applying deep learning models for analyzing sensor data in machinery is a fundamental step toward developing predictive maintenance strategies.
Aroui Tarek, Dorbez Fradj
doaj   +1 more source

Comparability between AI and human cognition and its role in psychological research and AI ethics

British Journal of Psychology, Volume 117, Issue 2, Page 785-789, May 2026.
Abstract With the advances in AI technology, comparison studies between humans and AI can not only enhance our understanding of information processing mechanisms underlying human cognition but also facilitate our understanding of AI systems' behaviour and interactions with humans.
Janet H. Hsiao
wiley   +1 more source

On the Optimal Selection of Mel‐Frequency Cepstral Coefficients for Voice Deepfake Detection

Expert Systems, Volume 43, Issue 5, May 2026.
ABSTRACT The continuous evolution of techniques for generating manipulated audio, known as voice deepfakes, and the widespread availability of tools that produce convincing forgeries have created an urgent need for reliable detection methods. This work considers the dimensionality of Mel‐Frequency Cepstral Coefficients (MFCCs) as a core design variable
Sergio A. Falcón‐López, Llanos Tobarra, Antonio Robles‐Gómez, Rafael Pastor‐Vargas   +3 more
wiley   +1 more source

CancerSeg-XA: Enhanced Breast Cancer Histo-pathology Segmentation Using Xception Backbone with Attention Mechanisms

Journal of Communications Software and Systems
Breast cancer remains a formidable health challenge requiring advanced computational tools for accurate diagnosis and treatment planning. This study hypothesizes that modifica-tions to the DeepLabV3+ architecture, such as incorporating an attention layer
Alaa Mohamed Youssef, Wessam Hassan El Behaidy, Aliaa Abdel-Haleim Abdel-Razik Youssif   +2 more
doaj   +1 more source

A deep learning–clinical nomogram hybrid for predicting sentinel lymph node metastasis in melanoma

Journal of the European Academy of Dermatology and Venereology, Volume 40, Issue 5, Page 811-822, May 2026.
We developed MISSLE, a deep learning–clinical nomogram hybrid model, to predict sentinel lymph node metastasis in invasive cutaneous melanoma with a high area under the receiver operating characteristic curve of 0.950 on the test set. MISSLE identifies key histopathological features and integrates AI for improved clinical decision‐making.
Minh‐Khang Le, Masataka Kawai, Tetsuo Kondo, Takashi Inozume, Yoshinori Muto, Youichi Ogawa, Shinji Shimada, Takashi Okamoto, Tatsuyoshi Kawamura   +8 more
wiley   +1 more source

ResNet50-Driven Quality Inspection for Recorder Musical Instrument

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
The manufacturer of a recorder musical instrument requires high-quality product. The aim is to produce precise tones and an aesthetic look at customer satisfaction. A major challenge encountered by manufacturers is traditional visual inspection.
Rizki Putra Prastio, Rodik Wahyu Indrawan, Vanesia Tasib, Zhilaan Abdurrasyid Rusmawan   +3 more
doaj   +1 more source

Cotton Plant Disease Prediction using Resnet50

, 2022
Plant diseases have become a major problem and have affected the economy adversely. Deep learning has helped on a large scale in detecting plant infections. Cotton is a widely grown crop and it is very important to detect the disease in it. Transfer learning plays a major role in the detection of infections which helps farmers save their plants from ...
openaire   +1 more source

Machine Learning‐Driven Construction of High‐Yielding Cucumber Plant Architectures in Greenhouse Environments

Plant Biotechnology Journal, Volume 24, Issue 5, Page 2917-2938, May 2026.
Schematic summary of the machine learning‐driven analysis for high‐yield cucumber architecture. This study employs machine learning methods to analyze key shoot and root traits, building a predictive model for yield. The analysis identifies an optimal plant architecture: a compact and sturdy shoot structure, combined with a narrow yet larger‐diameter ...
Cuifang Zhu, Hongjun Yu, Caili Zhao, Hongyang Wu, Xiaoyang Wan, Tao Lu, Yang Li, Weijie Jiang, Qiang Li   +8 more
wiley   +1 more source

Shorebird responses to fine‐scale water level fluctuations and macrofauna biomass in a newly constructed freshwater wetland

Restoration Ecology, Volume 34, Issue 4, May 2026.
Abstract Introduction Restoration of marine and freshwater wetlands for shorebirds is essential for the recovery of their declining populations. An ongoing approach is to restore shorebird habitats by large‐scale engineering, expecting the return of birds once suitable abiotic conditions are (re)established.
Lars Ursem, Elisabeth S. Bakker, Hui Jin, Casper H. A. van Leeuwen   +3 more
wiley   +1 more source