Results 41 to 50 of about 4,886 (174)

Sex Prediction From the Clavicle Using Computerized Tomography Images via Traditional and Hybrid Deep Learning Models

Clinical Anatomy, EarlyView.
ABSTRACT The aim of this study is to perform high accuracy sex prediction from clavicle images using proposed hybrid deep learning models and traditional deep learning models. The clavicle of 807 female and 805 male individuals obtained from Computed Tomography were segmented in 3D format and saved in jpeg format as superior–inferior and right–left ...
Yusuf Secgin, Muhammet Cakmak, Deniz Senol, Seren Kaya, Oğuzhan Oztürk, Oğuzhan Harmandaoğlu, Hatice Yenigül, Eslem Yaren Bıyık, Omer Onbaş   +8 more
wiley   +1 more source

An intrusion detection method based on depthwise separable convolution and attention mechanism

物联网学报, 2023
In order to improve the accuracy of multi-classification in network intrusion detection, an intrusion detection method was proposed based on depthwise separable convolution and attention mechanism.By constructing a cascade structure combining depthwise ...
Zhifei ZHANG, Feng LIU, Yiyang GE, Shuo LI, Yu ZHANG, Ke XIONG   +5 more
doaj   +2 more sources

From structural design to model compression: Research progress on lightweight algorithms for motor imagery brain–computer interfaces

Journal of Intelligent Medicine, EarlyView.
Lightweight Motor Imagery BCI Decoding: From Structural Design to Model Compression. This graphical abstract summarizes the motivation, principal strategies, and deployment benefits of lightweight motor imagery brain–computer interface decoding. Structural‐level lightweight designs, including depthwise separable, multi‐branch, and dilated convolutions,
Yijie Zhou, Zhuoyue Chu, Shengcui Cheng, Mingming Zhang, Long Chen, Zhongpeng Wang   +5 more
wiley   +1 more source

From ACR O‐RADS 2022 to Explainable Deep Learning

Journal of Ultrasound in Medicine, EarlyView.
Objectives The 2022 update of the Ovarian‐Adnexal Reporting and Data System (O‐RADS) improves risk stratification of adnexal lesions; however, radiologist interpretation remains subject to inter‐observer variability and conservative diagnostic thresholds.
Ali Abbasian Ardakani, Afshin Mohammadi, Alisa Mohebbi, Anushya Vijayananthan, Sook Sam Leong, Yi Ting Lim, Mohd Kamil Bin Mohamad Fabell, Gernot Hudelist, Balint Balogh, Marlina Tanty Ramli Hamid, U Rajendra Acharya, Sepideh Hatamikia   +11 more
wiley   +1 more source

Automatic insect identification, counting, and monitoring techniques: a review

Pest Management Science, EarlyView.
Automated insect monitoring increasingly integrates optical, acoustic, infrared, radar, electrostatic, and biosensing technologies with artificial intelligence. No single approach is universally optimal; reliable deployment depends on task‐specific validation, representative datasets, robustness under field conditions, energy autonomy, connectivity ...
Mariano González García, Juan Carlos Noguera Polania, Rosana González Combarros, José Ignacio López Sánchez   +3 more
wiley   +1 more source

Lightweight Convolutional Network for Bearing Fault Diagnosis

Journal of Harbin University of Science and Technology
In the field of bearing fault diagnosis, many convolutional models with excellent performance face challenges in industrial applications due to deployment cost constraints.
LIU Hui, LI Yang, HOU Yimin
doaj   +1 more source

NanoSentry: An Edge‐Deployable Unified Neural Architecture for Multi‐Domain Industrial Prognostics and Health Management

Artificial Intelligence for Engineering, EarlyView.
NanoSentry, a sub‐50 KiB unified architecture for multi‐domain prognostics, matches or outperforms models 4.5× $4.5\times $ larger across turbofan, battery, and bearing benchmarks while reducing end‐of‐life prediction error up to 5.8× $5.8\times $. Physical STM32H7 deployment confirms sub‐3 ms inference and up to 26 KiB peak SRAM without quantisation ...
Naem Azam Chowdhury, Abu Nasek, Khan Prottoy, Md Hamid Borkot Tulla, Jafor Sadik Chowdhury   +4 more
wiley   +1 more source

A Lightweight Deep Neural Network for Individual Leopard Identification: Supporting Movement Ecology in the Taihang Mountains of Henan

Integrative Zoology, EarlyView.
We developed LeoNet, a lightweight deep learning model for leopard individual identification. It achieved 97.42% accuracy and was robust to age‐related pattern changes and unfamiliar individuals. Applied to camera‐trap data from the Taihang Mountains, LeoNet identified 41 wild North China leopards and generated individual‐level records to support ...
Jing He, Guoqing Shangguan, Yu Li, Fuming Ma, Zhishu Xiao, Mingliang Fan, Zhuo Chen, Junzhan Ren, Yingfeng Ren, Yunlong Wang, Tianping Wang, Hua Yang, Hualei Shen, Xiaohong Chen   +13 more
wiley   +1 more source

Efficient Pediatric Pneumonia Diagnosis Using Depthwise Separable Convolutions [PDF]

SN Computer Science, 2020
Pneumonia is the leading cause of death in children worldwide. A fast and accurate pneumonia diagnosis system can be helpful in saving a pediatric patient’s life and ensuring their long-term health. In recent years, A.I. research has attempted to develop reliable deep learning models for detecting pneumonia in chest X-ray images.
openaire   +2 more sources

Pengenalan Gambar Braille Menggunakan Depthwise Separable Convolutional Neural Network

Techno.Com
Huruf Braille adalah huruf yang memiliki sistem tulisan yang menggunakan indra peraba untuk menggunakannya dan umum digunakan oleh penyandang tunanetra.
Kevin Maulana Afriyanto, Abas Setiawan
doaj   +1 more source