Results 21 to 30 of about 1,376 (159)

Memristive In-Memory Object Detection with 128 Mb C-Doped Ge₂Sb₂Te₅ PCM Chip. [PDF]

Adv Sci (Weinh)
A memristive in‐memory object detection system is presented for edge computing based on a 128 Mb phase change memory chip (40 nm, 99.99999 % yield) enabling in‐memory vector‐matrix multiplication and max computation. A novel mixed‐precision weight mapping reduces analog‐to‐digital‐converter energy by 22.3×.
Xie C, Li Y, Yan L, Song S, Chen H, Qi R, Li X, Zhu Y, Yu L, Yan B, Tao Y, Feng G, Yang Y, Song Z.   +13 more
europepmc   +2 more sources

Welding Spot Detection Method for Body in White Based on Improved YOLOv2 [PDF]

Jisuanji gongcheng, 2020
The machine-vision-based automatic detection methods for the welding spots of body in white provides an effective way to control the quality of the welding.However,due to the influence of light pollution,the machine vision system of the automatic ...
HE Zhicheng, WANG Zhenxing
doaj   +1 more source

Automatic Detection of Lung Nodules on Computer Tomography Scans with a Deep Direct Regression Method [PDF]

Journal of Artificial Intelligence and Data Mining, 2022
Deep-learning-based approaches have been extensively used in detecting pulmonary nodules from computer Tomography (CT) scans. In this study, an automated end-to-end framework with a convolution network (Conv-net) has been proposed to detect lung nodules ...
Kh. Aghajani
doaj   +1 more source

An Accurate and Fast Animal Species Detection System for Embedded Devices

IEEE Access, 2023
Encounters between humans and wildlife often lead to injuries, especially in remote wilderness regions, and highways. Therefore, animal detection is a vital safety and wildlife conservation component that can mitigate the negative impacts of these ...
Mai Ibraheam, Kin Fun Li, Fayez Gebali
doaj   +1 more source

PP-YOLOv2: A Practical Object Detector

CoRR, 2021
Being effective and efficient is essential to an object detector for practical use. To meet these two concerns, we comprehensively evaluate a collection of existing refinements to improve the performance of PP-YOLO while almost keep the infer time unchanged.
Xin Huang, Xinxin Wang, Wenyu Lv, Xiaying Bai, Xiang Long, Kaipeng Deng, Qingqing Dang, Shumin Han, Qiwen Liu, Xiaoguang Hu, Dianhai Yu, Yanjun Ma, Osamu Yoshie   +12 more
openaire   +2 more sources

Improved YOLOv3-Based Bridge Surface Defect Detection by Combining High- and Low-Resolution Feature Images

Buildings, 2022
Automatic bridge surface defect detection is of wide concern; it can save human resources and improve work efficiency. The object detection algorithm, especially the You Only Look Once (YOLO) series of networks, has important potential in real-time ...
Shuai Teng, Zongchao Liu, Xiaoda Li
doaj   +1 more source

Development of Combination Methods for Detecting Malignant Uptakes Based on Physiological Uptake Detection Using Object Detection With PET-CT MIP Images

Frontiers in Medicine, 2020
Deep learning technology is now used for medical imaging. YOLOv2 is an object detection model using deep learning. Here, we applied YOLOv2 to FDG-PET images to detect the physiological uptake on the images. We also investigated the detection precision of
Masashi Kawakami, Kenji Hirata, Sho Furuya, Kentaro Kobayashi, Hiroyuki Sugimori, Keiichi Magota, Chietsugu Katoh, Chietsugu Katoh   +7 more
doaj   +1 more source

Multi-object detection method for vehicles based on improved YOLOv3 model

Xi'an Gongcheng Daxue xuebao, 2021
To solve the problems of low detection rate and poor robustness of near and far object on real road environment, YOLOv3-Y based on the Darknet-53 feature extraction network model was proposed.
Liping MA, Xin YUN, Wenzhe MA, Hongwei ZHANG   +3 more
doaj   +1 more source

Diagnostic Accuracy of Deep Learning Models in Detecting Peri-Implant Marginal Bone Loss: A Systematic Review and Meta-Analysis. [PDF]

Clin Oral Implants Res
ABSTRACT Background Peri‐implantitis is a common implant complication requiring early detection to prevent bone loss and implant failure. Deep learning models show promise for enhancing radiographic diagnosis. Objectives This review systematically evaluated the diagnostic performance of deep learning models in detecting peri‐implant marginal bone loss ...
Atieh MA, Shah M, Hakam A, AlAli F, AlSayed S, Tawse-Smith A, Alsabeeha NHM.   +6 more
europepmc   +2 more sources

Optimized YOLOv2 based vehicle classification and tracking for intelligent transportation system

Results in Control and Optimization, 2021
The prevailing real-time system used for vehicle detection and classification using deep learning techniques accuracy diminishes due to its background, illumination variation, occlusion, and variation of vehicle sizes in a scene.
Kavitha N., Chandrappa D.N.
doaj   +1 more source