A Deep Learning-Based Object Representation Algorithm for Smart Retail Management

Journal of The Institution of Engineers (India) Series B, Год журнала: 2024, Номер 105(5), С. 1121 - 1128

Опубликована: Апрель 6, 2024

Язык: Английский

---

ADVANCED SHOPLIFTING PREVENTION AND ALERT STSYEM

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT, Год журнала: 2024, Номер 08(05), С. 1 - 5

Опубликована: Май 12, 2024

Detecting human beings accurately in a visual surveillance system is crucial for diverse application areas including abnormal event detection, gait characterization, congestion analysis, person identification, gender classification and fall detection elderly people. The first step of the process to detect an object which motion. Object could be performed using YOLOv7, optical flow spatio-temporal filtering techniques. Once detected, moving classified as being shape-based, texture-based or motion-based features. A comprehensive review with comparisons on available techniques detecting videos presented this paper. characteristics few benchmark datasets well future research directions have also been discussed. We can use camera Human Motion Detection. Camera used catch live images area it implemented, if any moving. captured are stored further work. If motion found video, computer will start recording, buzz alarm send SMS people listed its database. In way provide security against misdeed. Keywords: SMS, E-mail, CCTV, SMTP, RFID

Язык: Английский

---

Surveillance 5.0: Next-Gen Security Powered by Quantum AI Optimization

Recent Research Reviews Journal, Год журнала: 2024, Номер 3(1), С. 113 - 124

Опубликована: Июнь 1, 2024

Surveillance 5.0, powered by Quantum AI Optimization, represents the highpoint of next-generation security, transforming traditional surveillance paradigms through fusion quantum-powered technologies and advanced artificial intelligence. Optimization stands as essential, revolutionizing security operations for enabling real-time threat detection, proactive response approaches, adaptive risk mitigation measures. Moreover, privacy preservation ethical governance plays a major role in ensuring that activities maintain higher rights. From monitoring to emergency coordination, 5.0 empowers organizations across diverse sectors safeguard assets, protect individuals, enhance societal resilience. Lastly, prospective applications underscore limitless potential with emerging such Internet Things (IoT), intelligence (AI), Blockchain, edge computing driving continuous innovation expanding frontiers capabilities. In summary, quantum leap forward harnessing interactions leverage protection, privacy, an increasingly complex interconnected world.

Язык: Английский

---

Research on Application of Multi-Target Tracking Algorithm Based on Improved Yolo in Target Tracking and Detection of Unmanned Storage Equipment

Опубликована: Янв. 10, 2024

Язык: Английский

---

Evaluating the Energy Efficiency of Few-Shot Learning for Object Detection in Industrial Settings

Опубликована: Май 13, 2024

Язык: Английский

---

Mapping Gaps in Sugarcane Fields in Unmanned Aerial Vehicle Imagery Using YOLOv5 and ImageJ

Applied Sciences, Год журнала: 2024, Номер 14(17), С. 7454 - 7454

Опубликована: Авг. 23, 2024

Sugarcane plays a pivotal role in the Brazilian economy as primary crop. This semi-perennial crop allows for multiple harvests throughout its life cycle. Given longevity, farmers need to be mindful of avoiding gaps sugarcane fields, these interruptions planting lines negatively impact overall productivity over years. Recognizing and mapping failures becomes essential replanting operations estimation. Due scale cultivation, manual identification prove impractical. Consequently, solutions utilizing drone imagery computer vision have been developed cover extensive areas, showing satisfactory effectiveness identifying gaps. However, recognizing small poses significant challenges, often rendering them unidentifiable. study addresses this issue by any size while allowing users determine gap size. Preliminary tests using YOLOv5 ImageJ 1.53k demonstrated high success rate, with 96.1% accuracy 50 cm or larger. These results are favorable, especially when compared previously published works.

Язык: Английский

---

Retail Enhancement Using Computer Vision Models

Опубликована: Июль 13, 2024

Язык: Английский

---

Evaluating the Performance of YOLO Object Detectors for Plant Disease Detection

Опубликована: Июль 23, 2024

Язык: Английский

---

Computer Vision Techniques for Taylor Bubble Detection and Velocity Measurement Using Yolo V8 and Optical Flow

Опубликована: Янв. 1, 2024

Язык: Английский

---

Corn Plant In-Row Distance Analysis Based on Unmanned Aerial Vehicle Imagery and Row-Unit Dynamics

Applied Sciences, Год журнала: 2024, Номер 14(22), С. 10693 - 10693

Опубликована: Ноя. 19, 2024

Uniform spatial distribution of plants is crucial in arable crops. Seeding quality affected by numerous parameters, including the working speed and vibrations seeder. Therefore, investigating effective rapid methods to evaluate seeding parameters affecting seeders’ performance high importance. With latest advancements unmanned aerial vehicle (UAV) technology, potential for acquiring accurate agricultural data has significantly increased, making UAVs an ideal tool scouting applications systems. This study investigates effectiveness utilizing different plant recognition algorithms applied UAV-derived images evaluating seeder based on detected spacings. Additionally, it examines impact unit analyzing accelerometer installed For image analysis, three approaches were tested: unsupervised segmentation method Visible Atmospherically Resistant Index (VARI), template matching (TM), a deep learning model called Mask R-CNN. The R-CNN demonstrated highest reliability at 96.7%, excelling detecting errors such as misses doubles, well feed index precision when compared ground-truth data. Although VARI-based TM outperformed recognizing double spacings, overall, was most promising. Vibration analysis indicated that seeder’s quality. These findings suggest areas improvements machine technology improve sowing operations.

Язык: Английский

---